Debian Science Project
Summary
Statistics
Науковий набір Debian — пакунки зі статистики

Цей збірний пакунок є частиною Наукового набору Debian (Debian Pure Blend "Debian Science") і встановлює пакунки, які стосуються статистичних обчислень. Ці задачі є загальними та корисними для будь-якої наукової діяльності. Пакунок залежить від багатьох дослідницьких пакунків також, як і від інших інструментів, які є корисними для статистичних обчислень. Більш того задачі з математики є запропонованими і потребують додаткового встановлення відповідного математичного програмного забезпечення.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Science to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Science mailing list

Links to other tasks

Debian Science Statistics packages

Official Debian packages with high relevance

apophenia-bin
Apophenia Statistical C Library -- binary package
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The Apophenia Statistical C Library is an open source C library for working with data sets and statistical models. It provides functions on the same level as those of the typical stats packages (such as OLS, probit, or singular value decomposition) but gives the user more flexibility to be creative in model-building.

Apophenia is meant to scale well, to comfortably work with gigabyte data sets, million-step simulations, or computationally-intensive agent-based models.

Apophenia builds upon the GNU Scientific and SQLite libraries, MySQL/mariaDB is also supported. The core functions are written in C, but experience has shown them to be easy to bind in Python, Julia, Perl, Ruby, etc. The source code is distributed under the GNU General Public License version 2 (GPL2).

This package provides several command line utility examples.

datamash
statistics tool for command-line interface
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GNU Datamash is a command-line program which performs basic numeric, textual and statistical operations on input textual data files. It is designed to be portable and reliable, and aid researchers to easily automate analysis pipelines, without writing code or even short scripts.

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elpa-ess
Emacs mode for statistical programming and data analysis
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Emacs Speaks Statistics (ESS) is an add-on package for GNU Emacs. It is designed to support editing of scripts and interaction with various statistical analysis programs such as R, S, S-Plus, SAS, Stata, BUGS/JAGS and Julia.

It provides the following features:

  • Editing source code (R, S, S-plus, SAS, BUGS/JAGS, Stata, Julia)
  • Syntactic indentation and highlighting of source code
  • Partial evaluation of code
  • Loading and error-checking of code
  • Source code revision maintenance
  • Batch execution (SAS, BUGS/JAGS)
  • Use of imenu to provide links to appropriate functions
  • Interacting with the process (R, S, S-plus, SAS, Stata, Julia)
  • Command-line editing
  • Searchable Command history
  • Command-line completion of R, S, S-plus object names and file names
  • Quick access to object lists and search lists
  • Transcript recording
  • Interface to the help system
  • Transcript manipulation (R, S, S-plus, Stata)
  • Recording and saving transcript files
  • Manipulating and editing saved transcripts
  • Re-evaluating commands from transcript files
  • Interaction with Help Pages and other Documentation (R)
  • Fast Navigation
  • Sending Examples to running ESS process
  • Fast Transfer to Further Help Pages
  • Help File Editing (R)
  • Syntactic indentation and highlighting of source code
  • Sending Examples to running ESS process
  • Previewing
libdistlib-java
Java library of statistical distribution functions
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This is a library written in Java, providing probability density function, cumulative distribution function, quantiles and random variate generation for several common statistical distributions.

littler
GNU R scripting and command-line front-end -- transition package
Maintainer: Dirk Eddelbuettel
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The 'r' (aka 'littler') program provides a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics.

While R can be used in batch mode, the r binary adds full support for both 'shebang'-style scripting (i.e. using a hashmark-exclamation-path expression as the first line in scripts) as well as command-line use in standard Unix pipelines. In other words, r provides the R language without the environment.

This virtual package ensures that 'r-cran-littler' is installed. Once that is done, this 'littler' package can be removed.

persalys
GUI for uncertainty treatment and variabilities management
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Persalys is a graphical user interface for OpenTURNS, dedicated to the treatment of uncertainty and the management of variabilities. The software is a tool between the computer simulation, probabilistic analyses and the data sciences. The interface is available in French or in English.

Persalys allows one to:

  • create mathematical models: analytical, coupling with an external model (finite elements, ...), FMU;
  • analyse the variability of one's parameters thanks to many methods and visualisation tools;
  • statistically analyse one's measuring data, infer probability distributions or create metamodels.
psignifit
Fitting and testing hypotheses about psychometric functions
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Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Data can either be read from text files or passed through a pipe.

Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests.

This is the command line version.

Please note: This is the legacy version 2.x of psignifit.

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pspp
Statistical analysis tool
Maintainer: Friedrich Beckmann
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PSPP is a program for statistical analysis of sampled data. It is a free replacement for the proprietary program SPSS.

PSPP supports T-tests, ANOVA, GLM, factor analysis, non-parametric tests, and other statistical features. PSPP produces statistical reports in plain text, PDF, PostScript, CSV, HTML, SVG, and OpenDocument formats.

PSPP has both text-based and graphical user interfaces. The PSPP user interface has been translated into a number of languages.

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python3-bayespy
variational Bayesian inference tools for Python
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BayesPy provides tools for Bayesian inference with Python. The user constructs a model as a Bayesian network, observes data and runs posterior inference. The goal is to provide a tool which is efficient, flexible and extendable enough for expert use but also accessible for more casual users.

This package provides the modules for Python 3

python3-hmmlearn
unsupervised learning and inference of Hidden Markov Models
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Hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and similar models see seqlearn.

python3-openturns
Python3 front-end of OpenTURNS (aka TUI)
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OpenTURNS is a powerful and generic tool to treat and quantify uncertainties in numerical simulations in design, optimization and control. It allows both sensitivity and reliability analysis studies:

  • defining the outputs of interest and decision criterion;
  • quantify and model the source of uncertainties;
  • propagate uncertainties and/or analyse sensitivity and
  • rank the sources of uncertainty

Targeted users are all engineers who want to introduce the probabilistic dimension in their so far deterministic studies.

This package provides the Python3 bindings to the library.

python3-pandas
data structures for "relational" or "labeled" data
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pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data:

  • Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet
  • Ordered and unordered (not necessarily fixed-frequency) time series data.
  • Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels
  • Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure

This package contains the Python 3 version.

The package is enhanced by the following packages: python3-bottleneck python3-sklearn-pandas
Please cite: McKinney, Wes: pandas: a Foundational Python Library for Data Analysis and Statistics (eprint) (2011)
python3-persalys
GUI for uncertainty treatment (Python bindings)
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Persalys is a graphical user interface for OpenTURNS, dedicated to the treatment of uncertainty and the management of variabilities. The software is a tool between the computer simulation, probabilistic analyses and the data sciences. The interface is available in French or in English.

Persalys allows one to:

  • create mathematical models: analytical, coupling with an external model (finite elements, ...), FMU;
  • analyse the variability of one's parameters thanks to many methods and visualisation tools;
  • statistically analyse one's measuring data, infer probability distributions or create metamodels.

This package contains the Python3 bindings.

python3-scipy
scientific tools for Python 3
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SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package.

SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others.

Registry entries: SciCrunch 
python3-statsmodels
Python3 module for the estimation of statistical models
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statsmodels Python3 module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for several distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem.

Please cite: Skipper Seabold and Josef Perktold: Statsmodels: Econometric and statistical modeling with python (eprint) (2010)
r-cran-abind
GNU R abind multi-dimensional array combination function
Maintainer: Dirk Eddelbuettel
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This package provides the abind function, a generalization of the cbind and rbind function in the R base package. The abind function takes a sequence of vectors, matrices, or arrays and produces a single array of the same or higher dimension.

r-cran-acepack
GNU R package for regression transformations
Maintainer: Dirk Eddelbuettel
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This package provides the functions ace() and avas() for GNU R which can be used to select regression transformations.

r-cran-afex
GNU R package for analyzing factorial experiments using ANOVA or mixed models
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The r-cran-afex package is a GNU R package providing convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated- measures), or mixed between-within (i.e., split- plot) ANOVAs for data in long format (i.e., one observation per row), potentially aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex uses type 3 sums of squares as default (imitating commercial statistical software).

r-cran-amore
GNU R: A MORE flexible neural network package
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This package was born to release the TAO robust neural network algorithm to the R users. It has grown and can be of interest for the users wanting to implement their own training algorithms as well as for those others whose needs lye only in the "user space".

r-cran-arm
Data Analysis Using Regression and Multilevel/Hierarchical Models
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R functions for processing 'lm', 'glm', 'svy.glm', 'merMod' and 'polr' outputs.

r-cran-bayesfactor
GNU R Bayes factors for t-tests, ANOVAs and contingency tables
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r-cran-bayesfactor is a GNU R package providing a suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one- way designs, general ANOVA designs, and linear regression.

r-cran-bayesm
GNU R package for Bayesian inference
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The bayesm package covers many important models used in marketing and micro-econometrics applications. The package includes:

  • Bayes Regression (univariate or multivariate dep var)
  • Multinomial Logit (MNL) and Multinomial Probit (MNP)
  • Multivariate Probit,
  • Multivariate Mixtures of Normals
  • Hierarchical Linear Models with normal prior and covariates
  • Hierarchical Multinomial Logits with mixture of normals prior and covariates
  • Bayesian analysis of choice-based conjoint data
  • Bayesian treatment of linear instrumental variables models
  • Analyis of Multivariate Ordinal survey data with scale usage heterogeneity (as in Rossi et al, JASA (01)).

For further reference, consult the authors' book, Bayesian Statistics and Marketing by Allenby, McCulloch and Rossi.

r-cran-bms
GNU R package for Bayesian model averaging for linear models
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r-cran-bms is a GNU Package for Bayesian model averaging for linear models with a wide choice of (customizable) priors. Built-in priors include coefficient priors (fixed, flexible and hyper-g priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches.

Please cite: Martin Feldkircher and Stefan Zeugner: Benchmark Priors Revisited: On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging. (eprint) IMF Working Papers 202:1-39 (2009)
r-cran-boot
GNU R package for bootstrapping functions from Davison and Hinkley
Maintainer: Dirk Eddelbuettel
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This package provides functions and datasets from the book "Bootstrap Methods and Their Applications" by A. C. Davison and D. V. Hinkley (1997, CUP). It was witten by Angelo Canty, and ported to R by Brian Ripley.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-bradleyterry2
GNU R package for using Bradley-Terry models
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Specify and fit the Bradley-Terry model, including structured versions in which the parameters are related to explanatory variables through a linear predictor and versions with contest-specific effects, such as a home advantage.

r-cran-ca
GNU R package for simple, multiple and joint correspondence analysis
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r-cran-ca is a GNU R package for computation and visualization of simple, multiple and joint correspondence analysis

r-cran-cairodevice
GNU R Cairo/Gtk2 device driver package
Maintainer: Dirk Eddelbuettel
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This CRAN package provides a Cairo/GTK2 graphics device for GNU R that, in addition to standalone functionality, can be used to create devices as embedded components in a GUI using a Gtk drawing area widget, e.g. using RGtk2.

r-cran-car
GNU R Companion to Applied Regression by John Fox
Maintainer: Dirk Eddelbuettel
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This package accompanies J. Fox, An R and S-PLUS Companion to Applied Regression, Sage, 2002. The package contains mostly functions for applied regression, linear models, and generalized linear models, with an emphasis on regression diagnostics, particularly graphical diagnostic methods. There are also some utility functions.

r-cran-caret
GNU R package for classification and regression training
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This GNU R package provides misc functions for training and plotting classification and regression models.

r-cran-chron
GNU R package for chronologically ordered objects
Maintainer: Dirk Eddelbuettel
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This package contains function for chronologically ordered objects to handle dates and time in GNU R.

r-cran-cluster
GNU R package for cluster analysis by Rousseeuw et al
Maintainer: Dirk Eddelbuettel
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This package provides functions and datasets for cluster analysis originally written by Peter Rousseeuw, Anja Struyf and Mia Hubert.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-coda
Output analysis and diagnostics for MCMC simulations in R
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This package provides output analysis and diagnostics for Markov Chain Monte Carlo simulations and estimations within R. It also includes some graphical analysis routines and a facility for importing output from BUGS (Bayes Using Gibbs Sampling), a popular tool for running MCMC simulations.

The related r-cran-mcmcpack package includes MCMC estimators for some common models in the social sciences.

r-cran-codetools
GNU R package providing code analysis tools
Maintainer: Dirk Eddelbuettel
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This package provides functions for code analysis for R.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-coin
GNU R package providing conditional inference procedures
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The r-cran-coin package is a GNU R package providing conditional inference procedures for the general independence problem including two- sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems.

r-cran-contfrac
GNU R package providing various utilities for evaluating continued fractions
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The contfrac package is a GNU R package providing various utilities for evaluating continued fractions.

r-cran-conting
GNU R package for Bayesian analysis of contingency tables
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r-cran-conting is a GNU Package for Bayesian analysis of complete and incomplete contingency tables.

r-cran-corpcor
GNU R for Estimation of Covariance and Correlation -- corpcor
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GNU R package which implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

r-cran-date
GNU R package for date handling
Maintainer: Dirk Eddelbuettel
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This CRAN package provides functions for handling dates, along with examples and documentation.

Note that this is a legacy package providing functionality that had been absent from R. However, more recent versions of R have more powerful date and datetime functionality in the base package, i.e. r-base-core under Debian.

r-cran-dbi
GNU R package providing a generic database interface
Maintainer: Dirk Eddelbuettel
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A generic database interface (DBI) definition for communication between R and relational database management systems -- similar to Perl's DBI system. All classes in this package are virtual and need to be extended by the various R/DBMS implementations as e.g. RMySQL.

r-cran-deldir
GNU R Delaunay Triangulation and Dirichlet (Voronoi) Tessellation
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This GNU R package calculates the Delaunay triangulation and the Dirichlet or Voronoi tessellation (with respect to the entire plane) of a planar point set. This package is used in Spatial Point Pattern analysis, model-fitting and simulation as it is done for instance in the package r-cran-spatstat.

r-cran-desolve
GNU R package providing functions that solve initial value problems
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The deSolve package is a GNU R package providing functions that solve initial value problems of a system of first-order ordinary differential equations (ODE), of partial differential equations (PDE), of differential algebraic equations (DAE), and of delay differential equations.

r-cran-eco
GNU R routines for Bayesian ecological inference
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This is a set of routines for GNU R that implement Imai and Lu's parametric and nonparametric Bayesian ecological inference algorithms using Markov chain Monte Carlo estimation. Ecological inference is a statistical technique designed to recover individual-level information from aggregate-level data.

The suggested r-cran-mcmcpack package includes other EI estimators that may be useful alternatives to those included in this package.

Package ‘eco’ was removed from the CRAN repository. The code was obtained from the archive.

r-cran-ecodist
GNU R package for dissimilarity-based ecological analysis
Maintainer: Dirk Eddelbuettel
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The ecodist package provides dissimilarity-based analysis functions including ordination and Mantel test functions, intended for use with spatial and community data.

r-cran-effects
GNU R graphical and tabular effects display for glm models
Maintainer: Dirk Eddelbuettel
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This package provides functions for 'effect' displays: Graphical and tabular effect displays, e.g., of interactions, for linear generalized linear, multinomial-logit, and proportional-odds logit models.

An earlier version was described in the article by Fox (2003) in the Journal of Statistical Software available at http://www.jstatsoft.org/v08/i15/

r-cran-elliptic
GNU R package providing elliptic and related functions
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The elliptic package is a GNU R package providing a suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions.

r-cran-energy
GNU R package for energy statistics for distribution comparison
Maintainer: Dirk Eddelbuettel
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The energy package implements E-statistics (energy) tests and statistics for comparing distributions: multivariate normality, multivariate distance components and k-sample test for equal distributions, hierarchical clustering by e-distances, multivariate independence tests, distance correlation, goodness-of-fit tests. Energy-statistics concept based on a generalization of Newton's potential energy is due to Gabor J. Szekely.

r-cran-erm
GNU R package for 'extended Rasch modelling'
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eRm fits Rasch models (RM), linear logistic test models (LLTM), rating scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), and linear partial credit models (LPCM). Missing values are allowed in the data matrix. Additional features are the ML estimation of the person parameters, Andersen's LR-test, item-specific Wald test, itemfit and personfit statistics including infit and outfit measures, various ICC and related plots, automated stepwise item elimination, simulation module for various binary data matrices. An eRm platform is provided at R-forge (see URL).

r-cran-estimability
GNU R package providing tools for determining estimability of linear functions
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The estimability package is a GNU R package providing tools for determining estimability of linear functions of regression coefficients, and 'epredict' methods that handle non-estimable cases correctly.

r-cran-expm
GNU R Computation of the matrix exponential and related quantities
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The matrix exponential GNU R package enables computation of the matrix exponential and related quantities.

Please cite: Christopher H. Jackson: Multi-State Models for Panel Data: The msm Package for R. Journal of Statistical Software 38(8):1-29 (2011)
r-cran-fastcluster
Fast hierarchical clustering routines for GNU R
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Fastcluster implements fast hierarchical, agglomerative clustering routines. Part of the functionality is designed as drop-in replacement for existing routines: “linkage” in the SciPy package “scipy.cluster.hierarchy”, “hclust” in R's “stats” package, and the “flashClust” package. It provides the same functionality with the benefit of a much faster implementation. Moreover, there are memory-saving routines for clustering of vector data, which go beyond what the existing packages provide. For information on how to install the Python files, see the file INSTALL in the source distribution.

Please cite: Daniel Müllner: fastcluster: Fast Hierarchical, Agglomerative Clustering Routines for R and Python. (eprint) Journal of Statistical Software 53(9):1-18 (2013)
r-cran-fbasics
GNU R package for financial engineering -- fBasics
Maintainer: Dirk Eddelbuettel
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This package of functions for financial engineering and computational finance is part of Rmetrics, a collection of packages written and compiled by Diethelm Wuertz.

fBasics provides basic statistical tests, distributions and other tools used by many of the Rmetrics packages.

r-cran-fcopulae
GNU R package for financial engineering -- fCopulae
Maintainer: Dirk Eddelbuettel
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This package of functions for financial engineering and computational finance is part of Rmetrics, a collection of packages written and compiled by Diethelm Wuertz.

fCopulae provides functions for (nonlinear) dependence structure modelling.

r-cran-fextremes
GNU R package for financial engineering -- fExtremes
Maintainer: Dirk Eddelbuettel
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This package of functions for financial engineering and computational finance is part of Rmetrics, a collection of packages written and compiled by Diethelm Wuertz.

fExtremes provides functions to analyze extreme values.

r-cran-fmultivar
GNU R package for financial engineering -- fMultivar
Maintainer: Dirk Eddelbuettel
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This package of functions for financial engineering and computational finance is part of Rmetrics, a collection of packages written and compiled by Diethelm Wuertz.

fMultivar provides multivariate analysis for financial time series.

r-cran-foptions
Пакунок GNU R для фінансового інжинірингу — fOptions
Maintainer: Dirk Eddelbuettel
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Пакет функцій для фінансового інжинірингу та обчислювальної фінансової справи, є частиною Rmetrics, набору пакунків, написаних і скомпільованих Дієллем Вюрцем.

fOptions надає функції для оцінки і хеджування звичайних і екзотичний опцій для одного або декількох активів.

r-cran-foreign
GNU R package to read/write data from other stat. systems
Maintainer: Dirk Eddelbuettel
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This package provides functions for reading and writing data stored by statistical packages such as Minitab, S, SAS, SPSS, Stata, ...

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-fportfolio
GNU R package for financial engineering -- fPortfolio
Maintainer: Dirk Eddelbuettel
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This package of functions for financial engineering and computational finance is part of Rmetrics, a collection of packages written and compiled by Diethelm Wuertz.

fPortfolio provides functions for portfolio and asset price modeling, drawdown statistics, value-at-risk and Markowitz portfolio construction.

r-cran-gam
Generalized Additive Models for R
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Functions for fitting and working with generalized additive models, as described in chapter 7 of “Statistical Models in S” (Chambers and Hastie (eds), 1991), and “Generalized Additive Models” (Hastie and Tibshirani, 1990).

r-cran-gdata
GNU R package with data manipulation tools by Greg Warnes et al
Maintainer: Dirk Eddelbuettel
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This package of R programming tools was written by Gregory Warnes with code contributions by Ben Bolker and Thomas Lumley.

This package used to be part of the gregmisc bundle packaged for Debian as r-cran-gregmisc.

r-cran-geepack
Generalized Estimating Equation Package for R
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Generalized estimating equations solver for parameters in mean, scale, and correlation structures, through mean link, scale link, and correlation link. Can also handle clustered categorical responses.

r-cran-ggplot2
implementation of the Grammar of Graphics
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ggplot2 combines the advantages of both base and lattice graphics. Conditioning and shared axes are handled automatically, and you can still build up a plot step by step from multiple data sources. It also implements a sophisticated multidimensional conditioning system and a consistent interface to map data to aesthetic attributes.

Please cite: Hadley Wickham: Link to publication (2009)
r-cran-glmnet
Lasso and Elastic-Net Regularized Generalized Linear Models
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Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper Introduction to Glmnet.

r-cran-gmodels
GNU R package with tools for model fitting by Greg Warnes et al
Maintainer: Dirk Eddelbuettel
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This package of R programming tools for model fitting was written by Gregory Warnes with code contributions by Ben Bolker and Thomas Lumley.

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r-cran-goftest
GNU R Classical Goodness-of-Fit Tests for Univariate Distributions
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This R package provides Cramer-Von Mises and Anderson-Darling tests of goodness-of-fit for continuous univariate distributions, using efficient algorithms.

r-cran-gplots
GNU R package with tools for plotting data by Greg Warnes et al
Maintainer: Dirk Eddelbuettel
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This package of R programming tools for plotting data was written by Gregory Warnes with code contributions by Ben Bolker and Thomas Lumley.

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r-cran-gregmisc
GNU R package with miscellaneous functions by Greg Warnes et al
Maintainer: Dirk Eddelbuettel
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This package of miscellaneous functions for GNU R that written by Gregory Warnes with code contributions by Ben Bolker, Bendix Carstensen, Don MacQueen, William Venables, Marc Schwartz, Ben Bolker, Ian Wilson, Kjetil Halvorsen, Arni Magnusson, Lodewijk Bonebakker, and others.

Most of the function in the gregmisc library fall into six general areas: permutations and combinations, tools for linear models, plots, data manipulation, and fixed or extended versions of existing functions.

Note that as of version 2.0.8, gregmisc's code is now provided by the new packages gdata, gmodels, gplots and gtools which contain all the code formerly provided by gregmisc. Unless any of your R code still loads the gregmisc package directly, and you thus need it to load the component packages, you can remove this package.

r-cran-gtools
GNU R package with R programming tools by Greg Warnes et al
Maintainer: Dirk Eddelbuettel
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r-cran-hdf5
GNU R package interfacing the NCSA HDF5 library
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This package provides the functions hdf5save and hdf5load which allow saving and loading of R variables in the Hierarchical Data Format (HDF) format. Lists, strings, vectors, matrices and higher-dimensional arrays are supported.

r-cran-hmisc
GNU R miscellaneous functions by Frank Harrell
Maintainer: Dirk Eddelbuettel
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The Hmisc library contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, translating SAS datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of S objects to LaTeX code, recoding variables, and bootstrap repeated measures analysis.

r-cran-hypergeo
GNU R package providing the Gaussian hypergeometric for complex numbers
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The r-cran-hypergeo package is a GNU R package providing the Gaussian hypergeometric function for complex numbers.

r-cran-its
GNU R package for handling irregular time series
Maintainer: Dirk Eddelbuettel
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This package contains an S4 class for handling irregular time series

r-cran-kernsmooth
GNU R package for kernel smoothing and density estimation
Maintainer: Dirk Eddelbuettel
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This package provides functions for kernel smoothing and density estimation corresponding to M.P. Wand and M.C. Jones, "Kernel Smoothing", 1995.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

URL: http://www.maths.unsw.edu.au/~wand

r-cran-lattice
GNU R package for 'Trellis' graphics
Maintainer: Dirk Eddelbuettel
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This package provides functions for 'Trellis' graphics -- a framework for data visualization developed at the Bell Labs by Rick Becker, Bill Cleveland et al, extending ideas presented in Bill Cleveland's 1993 book 'Visualizing Data'.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-latticeextra
GNU R package of additional graphical displays based on lattice
Maintainer: Dirk Eddelbuettel
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This CRAN package provides generic functions and standard methods for trellis-based displays.

r-cran-lavaan
GNU R package for latent variable analysis -- lavaan
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This package supplies latent variable analysis for R. One can use lavaan to estimate a large variety of multivariate statistical models, including path analysis, confirmatory factor analysis, structural equation modeling and growth curve models.

r-cran-lhs
GNU R Latin Hypercube Samples
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This package provides a number of methods for creating and augmenting Latin Hypercube Samples.

Latin hypercube sampling (LHS) is a statistical method for generating a sample of plausible collections of parameter values from a multidimensional distribution. The sampling method is often used to construct computer experiments.

r-cran-lme4
GNU R package for linear mixed effects model fitting
Maintainer: Dirk Eddelbuettel
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This CRAN package provides S4 classes and methods for fitting and examining linear mixed effects models (also called multilevel models, panel data models, and several other names) and generalized linear mixed effects models.

r-cran-lmtest
GNU R package for diagnostic checking in linear models
Maintainer: Dirk Eddelbuettel
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This package provides a collection of tests, data sets and examples for diagnostic checking in linear regression models.

r-cran-logspline
GNU R package providing routines for the logspline density estimation
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The logspline package provides routines for logspline density estimation based on the algorithm from Stone et. al. (1997).

r-cran-lsmeans
GNU R package providing least-squares means for various classes of models
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The r-cran-lsmeans package is a GNU R package to obtain least-squares means for many linear, generalized linear, and mixed models. Additionally it can compute contrasts or linear functions of least- squares means, and comparisons of slopes.

r-cran-mapdata
GNU R support for producing geographic maps (supplemental data)
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This package provides facilities for easily producing high-resolution maps based on data sets in the GNU R statistical computing environment. It includes high-resolution map data for the entire world, along with maps of China (including provincial boundaries) and a higher-resolution map of New Zealand and a number of nearby Pacific islands.

The suggested r-cran-mapproj package adds facilities for calculating geographic projections, which are used by mapmakers to compensate for the inaccuracies inherent in projecting a spheroid's surface onto a two-dimensional plane.

r-cran-mapproj
GNU R support for cartographic projections of map data
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This package provides facilities for easily producing cartographic projections of maps based on data sets in the GNU R statistical computing environment. Projections are used by mapmakers to compensate for the inaccuracies inherent in projecting a spheroid's surface onto a two-dimensional plane.

r-cran-maps
GNU R support for producing geographic maps
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This package provides facilities for easily producing maps based on data sets in the GNU R statistical computing environment.

The r-cran-maps package includes map data for the United States (including state and county-level maps), New Zealand, and a world map; additional maps (including a higher-resolution world map) are available in the suggested r-cran-mapdata package.

The suggested r-cran-mapproj package adds facilities for calculating geographic projections, which are used by mapmakers to compensate for the inaccuracies inherent in projecting a spheroid's surface onto a two-dimensional plane.

r-cran-maptree
GNU R mapping, pruning, and graphing tree models
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This GNU R package provides functions with example data for graphing, pruning, and mapping models from hierarchical clustering, and classification and regression trees.

r-cran-mass
GNU R package of Venables and Ripley's MASS
Maintainer: Dirk Eddelbuettel
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The MASS package provides functions and datasets to support the book 'Modern Applied Statistics with S' (4th edition) by W.N. Venables and B.D. Ripley. The following URL provides more details about the book: URL: http://www.stats.ox.ac.uk/pub/MASS4

The package is enhanced by the following packages: r-cran-pscl
r-cran-matchit
GNU R package of nonparametric matching methods
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MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2004) for improving parametric statistical models by preprocessing data with nonparametric matching methods.

MatchIt implements a wide range of sophisticated matching methods, making it possible to greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical modeling assumptions. The software also easily fits into existing research practices since, after preprocessing with MatchIt, researchers can use whatever parametric model they would have used without MatchIt, but produce inferences with substantially more robustness and less sensitivity to modeling assumptions. MatchIt is an R program, and also works seamlessly within Zelig.

r-cran-matrix
GNU R package of classes for dense and sparse matrices
Maintainer: Dirk Eddelbuettel
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This CRAN package provides S4 classes and methods for numerical linear algebra using dense or sparse matrices. The sparse matrix implementation uses code from the LDL sparse matrix package and code from the Metis package of partitioning algorithms.

r-cran-mcmcpack
R routines for Markov chain Monte Carlo model estimation
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This is a set of routines for GNU R that implement various statistical and econometric models using Markov chain Monte Carlo (MCMC) estimation, which allows "solving" models that would otherwise be intractable with traditional techniques, particularly problems in Bayesian statistics (where one or more "priors" are used as part of the estimation procedure, instead of an assumption of ignorance about the "true" point estimates), although MCMC can also be used to solve frequentist statistical problems with uninformative priors. MCMC techniques are also preferable over direct estimation in the presence of missing data.

Currently implemented are a number of ecological inference (EI) routines (for estimating individual-level attributes or behavior from aggregate data, such as electoral returns or census results), as well as models for traditional linear panel and cross-sectional data, some visualization routines for EI diagnostics, two item-response theory (or ideal-point estimation) models, metric, ordinal, and mixed-response factor analysis, and models for Gaussian (linear) and Poisson regression, logistic regression (or logit), and binary and ordinal-response probit models.

The suggested packages (r-cran-bayesm, -eco, and -mnp) contain additional models that may also be useful for those interested in this package.

The package is enhanced by the following packages: r-cran-mcmc r-cran-mnp
r-cran-mgcv
GNU R package for multiple parameter smoothing estimation
Maintainer: Dirk Eddelbuettel
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This package provides functions for generalised additive models (GAMs) and other generalized ridge regression problems with multiple smoothing parameter selection by GCV or UBRE. It includes an implementation (not a clone) of gam().

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-misc3d
GNU R collection of 3d plot functions and rgl-based isosurfaces
Maintainer: Dirk Eddelbuettel
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This CRAN package provides a collection of miscellaneous 3d plots, including rgl-based isosurfaces:

 contour3d     Uses rgl to render isosurfaces, or three-dimensional
               contours, computed by the marching cubes algorithm.
 image3d       Crude 3d analog of image() using rgl to plot points on a
               three dimensional grid representing values in a three
               dimensional array. Assumes high values are inside and
               uses alpha blending to make outside points more
               transparent.
 lines3d       Draws connected line segments in an rgl window.
 parametric3d  Plots a two-parameter surface in three dimensions in
               rgl.  Based on Mathematica's Param3D
 slices3d      Uses tkrplot to create an interactive slice view of three or
               four dimensional volume data, such as MRI data.
r-cran-mnp
GNU R package for fitting multinomial probit (MNP) models
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MNP is an R package that fits Bayesian Multinomial Probit (MNP) models via Markov chain Monte Carlo (MCMC). Along with the standard multinomial probit model, it can also fit models with different choice sets for each observation and complete or partial ordering of all the available alternatives. The estimation is based on the efficient marginal data augmentation algorithm that is developed by Imai and van Dyk (2004).

r-cran-modelmetrics
GNU R Rapid Calculation of Model Metrics
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This GNU R package provides a collection of metrics for evaluating models written in C++ using 'Rcpp'.

r-cran-modeltools
GNU R package providing a collection of tools to deal with statistical models
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The r-cran-modeltools package is a GNU R package providing a collection of tools to deal with statistical models.

r-cran-msm
GNU R Multi-state Markov and hidden Markov models in continuous time
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Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.

Please cite: Christopher H. Jackson: Multi-State Models for Panel Data: The msm Package for R. Journal of Statistical Software 38(8):1-29 (2011)
r-cran-multcomp
GNU R package for multiple comparison procedures
Maintainer: Dirk Eddelbuettel
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This package provides functions to perform multiple comparison tests and simultaneous confidence intervals in one-way layout testing setups.

r-cran-mvnormtest
GNU R package for multivariate normality test
Maintainer: Dirk Eddelbuettel
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The mvnormtest package provides a generalization of the Shapiro-Wilk test for multivariate variables.

r-cran-mvtnorm
GNU R package to compute multivariate Normal and T distributions
Maintainer: Dirk Eddelbuettel
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This package provides a collection of functions to compute the multivariate Normal and T distributions.

r-cran-nlme
GNU R package for (non-)linear mixed effects models
Maintainer: Dirk Eddelbuettel
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This package provides functions to fit and compare linear and non-linear mixed-effects models.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-nmf
GNU R framework to perform non-negative matrix factorization
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This package implements a set of previously published algorithms and seeding methods, and provides a framework to test, develop and plug new/custom algorithms. Most of the built-in algorithms have been optimized, and the main interface function provides parallel computations on multicore machines.

Please cite: Renaud Gaujoux and Cathal Seoighe: A flexible R package for nonnegative matrix factorization. (PubMed,eprint) BMC Bioinformatics 11(1):367 (2010)
r-cran-pbapply
GNU R package providing progress bars for vectorized R functions
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The r-cran-pbapply package is a GNU R package providing progress bars for vectorized R functions.

r-cran-pbivnorm
GNU R package for calculating probabilities from a bivariate normal CDF
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The r-cran-pbivnorm package is a GNU R package providing a vectorized R function for calculating probabilities from a standard bivariate normal CDF

r-cran-permute
R functions for generating restricted permutations of data
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Implements a set of restricted permutation designs for freely exchangeable, line transects (time series), and spatial grid designs plus permutation of blocks (groups of samples). ‘permute’ also allows split-plot designs, in which the whole-plots or split-plots or both can be freely-exchangeble or one of the restricted designs. The permute package is modelled after the permutation schemes of Canoco 3.1 by Cajo ter Braak.

r-cran-pscl
GNU R package for discrete data models
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This package consists of R functions developed at the Political Science Computational Laboratory at Stanford University; it currently includes models for count data (hurdle regression and zero-inflated negative binomial and Poisson models), ordinal probit and logit (also available in MASS via polr), and an item-response theory model. Also included are Vuong tests for non-nested hypothesis testing and convenience functions for handling roll-call vote matrices.

r-cran-psy
GNU R procedures for psychometrics
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This package includes several procedures used in psychometrics and scaling, including:

  • Cohen's Kappa and weighted Kappa (two-rater agreement tests)
  • Cronbach's Alpha (an item-reliability test)
  • Focused Principal Components Analysis
  • Intraclass correlation coefficients
  • Light's Kappa (an N-rater agreement test)
  • Screeplots and graphical representations of principal components
r-cran-qtl
GNU R package for genetic marker linkage analysis
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R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental crosses. It is implemented as an add-on-package for the freely available and widely used statistical language/software R (see http://www.r-project.org).

The development of this software as an add-on to R allows one to take advantage of the basic mathematical and statistical functions, and powerful graphics capabilities, that are provided with R. Further, the user will benefit by the seamless integration of the QTL mapping software into a general statistical analysis program. The goal is to make complex QTL mapping methods widely accessible and allow users to focus on modeling rather than computing.

A key component of computational methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing genotype data. The main HMM algorithms, with allowance for the presence of genotyping errors, for backcrosses, intercrosses, and phase-known four-way crosses were implemented.

The current version of R/qtl includes facilities for estimating genetic maps, identifying genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, by interval mapping (with the EM algorithm), Haley-Knott regression, and multiple imputation. All of this may be done in the presence of covariates (such as sex, age or treatment). One may also fit higher-order QTL models by multiple imputation.

Please cite: Karl W. Broman, Hao Wu, Saunak Sen and Gary A. Churchill: R/qtl: QTL mapping in experimental crosses. (PubMed,eprint) Bioinformatics 19:889-890 (2003)
Registry entries: Bio.tools  SciCrunch  Bioconda 
r-cran-quadprog
GNU R package for solving quadratic programming problems
Maintainer: Dirk Eddelbuettel
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This CRAN package provides functions and documentation for solving quadratic programming problems in GNU R.

r-cran-qvcalc
GNU R quasi variances for factor effects in statistical models
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This GNU R package provides functions to compute quasi variances and associated measures of approximation error in statistical models.

r-cran-randomfieldsutils
utilities for the simulation and analysis of random fields
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Various utilities are provided that might be used in spatial statistics and elsewhere. It delivers a method for solving linear equations that checks the sparsity of the matrix before any algorithm is used. Furthermore, it includes the Struve functions.

r-cran-raschsampler
GNU R package for sampling binary matrices with fixed margins
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This package implements an MCMC algorithm for sampling of binary matrices with fixed margins complying to the Rasch model. Its stationary distribution is uniform. The algorithm also allows for square matrices with fixed diagonal.

r-cran-rcmdr
GNU R platform-independent basic-statistics GUI
Maintainer: Dirk Eddelbuettel
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This package provides a simple GUI, based on the GNU interface to Tcl/Tk, that is suitable for teaching introductory statistics.

r-cran-relimp
GNU R package for inference on relative importance of regressors
Maintainer: Dirk Eddelbuettel
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This package provides functions to facilitate inference on the relative importance of predictors in a linear or generalized linear model.

r-cran-reshape2
Flexibly reshape data: a reboot of the reshape package
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Reshape lets you flexibly restructure and aggregate data using just two functions: melt and cast.

Reshape (hopefully) makes it easy to do what you have been struggling to do with tapply, by, aggregate, xtabs, apply and summarise. It is also useful for getting your data into the correct structure for lattice or ggplot plots.

r-cran-rggobi
GNU R package for the GGobi data visualization system
Maintainer: Dirk Eddelbuettel
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This Debian package contains the R package for access to the ggobi data visualization system for high-dimensional data from within GNU R.

See http://www.ggobi.org/rggobi for rggobi, http://www.ggobi.org/ggobi and http://www.r-project.org for GNU R.

r-cran-rgl
GNU R package for three-dimensional visualisation using OpenGL
Maintainer: Dirk Eddelbuettel
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This package provides functions implementing a new graphics device suitable for visualisation of GNU R objects in three dimensions using the OpenGL libraries.

r-cran-rgtk2
GNU R binding for Gtk2
Maintainer: Dirk Eddelbuettel
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This package provides facilities in the S language (i.e. the language which GNU R provides) for programming graphical interfaces using Gtk, the GNOME GUI toolkit.

This package extends and updates the previous r-omegahat-rgtk package to the 2.8 release of the Gtk libraries.

r-cran-rinside
GNU R package to embed R in C++ application
Maintainer: Dirk Eddelbuettel
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The 'RInside' packages makes it easier to have "R inside" your C++ application by providing a C++ wrapper class providing the R interpreter.

As R itself is embedded into your application, a shared library build of R is required. This works on Linux, OS X and even on Windows provided you use the same tools used to build R itself.

Numerous examples are provided in the eight subdirectories of the examples/ directory of the installed package: standard, mpi (for parallel computing) qt (showing how to embed 'RInside' inside a Qt GUI application), wt (showing how to build a "web-application" using the Wt toolkit), armadillo (for 'RInside' use with 'RcppArmadillo') and eigen (for 'RInside' use with 'RcppEigen'). The example use GNUmakefile(s) with GNU extensions, so a GNU make is required (and will use the GNUmakefile automatically).

Doxygen-generated documentation of the C++ classes is available at the 'RInside' website as well.

r-cran-rmpi
GNU R package interfacing MPI libraries for distributed computing
Maintainer: Dirk Eddelbuettel
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This CRAN package provides an interface to the MPI (Message-Passing Interface) API. It also provides an interactive R slave environment in which distributed statistical computing can be carried out.

r-cran-rms
GNU R regression modeling strategies by Frank Harrell
Maintainer: Dirk Eddelbuettel
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Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.

See Frank Harrell (2001), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/Rrms.

r-cran-rmysql
GNU R package providing a DBI-compliant interface to MySQL
Maintainer: Dirk Eddelbuettel
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The package implements access to MySQL databases via the DBI interface of R.

r-cran-rodbc
GNU R package for ODBC database access
Maintainer: Dirk Eddelbuettel
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This CRAN package provides access to any Open DataBase Connectivity (ODBC) accessible database.

The package should be platform independent and provide access to any database for which a driver exists. It has been tested with MySQL and PostgreSQL on both Linux and Windows (and to those DBMSs on Linux hosts from R under Windows), Microsoft Access, SQL Server and Excel spreadsheets (read-only), and users have reported success with connections to Oracle and DBase.

Usage is covered in the R Data Import/Export manual (available via the r-doc-pdf, r-doc-html and r-doc-info packages).

r-cran-rpart
GNU R package for recursive partitioning and regression trees
Maintainer: Dirk Eddelbuettel
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This package provides functions to recursive partitioning and regression trees.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

URL (of the S-Plus original): http://www.mayo.edu/hsr/Sfunc.html

r-cran-rquantlib
GNU R package interfacing the QuantLib finance library
Maintainer: Dirk Eddelbuettel
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This CRAN package provides an interface for GNU R to the QuantLib library for modeling, trading, and risk management of financial assets.

r-cran-rsdmx
GNU R package for the Statistical Data and Metadata Exchange (SDMX) framework
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This package provides a set of classes and methods to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework, currently focusing on the SDMX XML standard format (SDMX-ML).

SDMX is an initiative to foster standards for the exchange of statistical information. It is sponsored by several major providers of statistical information: the Bank for International Settlements, the European Central Bank, Eurostat (the statistical office of the European Union), the International Monetary Fund (IMF), the Organisation for Economic Co-operation and Development (OECD), the United Nations Statistics Division, the United Nations Educational, Scientific and Cultural Organization and the World Bank.

The package can therefore be used to download statistical information from the servers of those organizations, and from those of several other institutions.

r-cran-rserve
GNU R Rserve tcp/ip server and sample clients
Maintainer: Dirk Eddelbuettel
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This package provide Rserve, a headless server for GNU R. Rserve acts as a socket server (TCP/IP or local sockets) which allows binary requests to be sent to R. Every connection has a separate workspace and working directory. Client-side implementations are available for popular languages such as C/C++ and Java, allowing any application to use facilities of R without the need of linking to R code. Rserve supports remote connection, user authentication and file transfer. A simple R client is included in this package as well.

URL: http://www.rosuda.org/Rserve/

r-cran-rsprng
GNU R interface to SPRNG (Scalable Parallel RNGs)
Maintainer: Dirk Eddelbuettel
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This package provides an interface to the SPRNG (Scalable Parallel Random Number Generator) library API, along with examples and documentation.

r-cran-sandwich
GNU R package for model-robust standard error estimates
Maintainer: Dirk Eddelbuettel
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This package contains model-robust standard error estimators for time series and longitudinal data.

r-cran-sem
GNU R functions for fitting structural equation models -- sem
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GNU R package supplying functions for fitting general linear structural equation models (with observed and latent variables) using the RAM approach, and for fitting structural equations in observed-variable models by two-stage least squares.

r-cran-sm
GNU R package for kernel smoothing methods
Maintainer: Dirk Eddelbuettel
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This CRAN package provides functions and documentation for kernel smoothing methods for GNU R. The functions are described in the book "Applied Smoothing Techniques for Data Analysis: The kernel approach with S-Plus illustrations" by Adrian W. Bowman & Adelchi Azzalini, Oxford UP, 1997.

r-cran-snow
GNU R package for 'simple network of workstations'
Maintainer: Dirk Eddelbuettel
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This package provide the 'simple network of workstations' (SNOW), an easy-to-use system for parallel computing in GNU R.

r-cran-spam
GNU R functions for sparse matrix algebra
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Set of functions for sparse matrix algebra. Differences with SparseM/Matrix are:

 1. only (essentially) one sparse matrix format supported,
 2. based on transparent and simple structure(s),
 3. tailored for MCMC calculations within GMRF.
 4. S3 and S4 like-"compatible"
Please cite: Reinhard Furrer and Stephan R. Sain: spam: A Sparse Matrix R Package with Emphasis on MCMC Methods for Gaussian Markov Random Fields. (eprint) Journal of Statistical Software 36(10):1-25 (2010)
r-cran-spatstat
GNU R Spatial Point Pattern analysis, model-fitting, simulation, tests
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A GNU R package for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Contains functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, and pixel images. Point process models can be fitted to point pattern data. Cluster type models are fitted by the method of minimum contrast. Very general Gibbs point process models can be fitted to point pattern data using a function ppm similar to lm or glm. Models may include dependence on covariates, interpoint interaction and dependence on marks. Fitted models can be simulated automatically. Also provides facilities for formal inference (such as chi-squared tests) and model diagnostics (including simulation envelopes, residuals, residual plots and Q-Q plots).

Please cite: Adrian Baddeley and Rolf Turner: Spatstat: an {R} package for analyzing spatial point patterns. Journal of Statistical Software 12(6):1-42 (2005)
r-cran-statmod
GNU R package providing algorithms and functions for statistical modeling
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This R package provides a collection of algorithms and functions to aid statistical modeling. Includes limiting dilution analysis (aka ELDA), growth curve comparisons, mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Also includes a number of advanced generalized linear model functions including new Tweedie and Digamma glm families and a secure convergence algorithm.

r-cran-strucchange
GNU R package for structural change regression estimation
Maintainer: Dirk Eddelbuettel
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This package functions for testing, dating and monitoring of structural change in linear regression relationships. The strucchange package features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, recursive/moving estimates) and F statistics, respectively. It is possible to monitor incoming data online using fluctuation processes.

Finally, the breakpoints in regression models with structural changes can be estimated together with confidence intervals. Emphasis is always given to methods for visualizing the data.

r-cran-survival
GNU R package for survival analysis
Maintainer: Dirk Eddelbuettel
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This package provides functions and datasets for survival analysis: descriptive statistics, two-sample tests, parametric accelerated failure models, Cox model. Delayed entry (truncation) is allowed for all models; interval censoring for parametric models.

This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.

r-cran-teachingdemos
GNU R Demonstrations for teaching and learning
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This package is a set of demonstration functions that can be used in a classroom to demonstrate statistical concepts, or on your own to better understand the concepts or the programming.

r-cran-timedate
GNU R package for financial engineering -- timeDate
Maintainer: Dirk Eddelbuettel
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This package provides functions for chronological and calendarical objects and is part of Rmetrics, a collection of packages for financial engineering and computational finance written and compiled by Diethelm Wuertz and others.

timeDate provides functions for chronological and calendarical objects.

r-cran-tkrplot
GNU R embedded Tk plotting device package
Maintainer: Dirk Eddelbuettel
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This CRAN package provides a Tk graphics device which enables embedding of GNU R plot() results inside a Tk widget.

r-cran-tseries
GNU R package for time-series analysis and comp. finance
Maintainer: Dirk Eddelbuettel
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This CRAN package provides additional time-series analysis functions, as well as several computational finance routines.

r-cran-vcd
GNU R Visualizing Categorical Data
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Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was inspired by the book "Visualizing Categorical Data" by Michael Friendly.

Please cite: David Meyer, Achim Zeileis and Kurt Hornik: The Strucplot Framework: Visualizing Multi-Way Contingency Tables with vcd. (eprint) Journal of Statistical Software 17(3):1-48 (2006)
r-cran-vcdextra
GNU R package providing extensions and additions to the vcd package
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The vcdExtra package is a GNU R package providing additional data sets, methods and documentation to complement the 'vcd' package for Visualizing Categorical Data and the 'gnm' package for Generalized Nonlinear Models. In particular, 'vcdExtra' extends mosaic, assoc and sieve plots from 'vcd' to handle 'glm()' and 'gnm()' models and adds a 3D version in 'mosaic3d'. Additionally, methods are provided for comparing and visualizing lists of 'glm' and 'loglm' objects. This package is now a support package for the book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer.

r-cran-vgam
GNU R package for estimating vector generalized additive models
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This package implements a variety of functions for estimating vector generalized additive models (VGAMs), as well as vector generalized linear models (VGLMs), reduced-rank VGLMs, and quadratic reduced-rank VGLMs.

Specific models that can be fit include a wide variety of categorical-response models (with nominal and ordinal dependent variables), bivariate binary-response models (bivariate logit/probit), and seemingly-unrelated regressions. The package also includes a number of standard and non-standard distribution functions of use to statisticians.

r-cran-xml
GNU R package for XML parsing and generation
Maintainer: Dirk Eddelbuettel
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This package provides facilities for the R language to

  • parse XML files, URLs and strings, using either the DOM (Document Object Model)/tree-based approach, or the event-driven SAX (Simple API for XML) mechanism;
  • generate XML content to buffers, files, URLs, and internal XML trees;
  • read DTDs as R objects.
r-cran-zelig
GNU R package providing a unified front-end for estimating statistical models
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With thousands of contributors who have written hundreds of packaged routines, R can deal with nearly any statistical problem. Although this high level of participation may be its greatest strength, the enormous diversity in approaches to statistical inference covered by R often results in a virtual babel of competing functions and inconsistent syntax.

To address these problems from a common perspective, the upstream authors have created Zelig, a single, easy-to-use program, with a unified framework and syntax, that can estimate, help interpret, and present the results of a large range of statistical methods. It literally is "everyone's statistical software" because Zelig uses R code from many researchers. They also hope it will become "everyone's statistical software" for applications, and they have designed it so that anyone can use it or add their methods to it. Zelig comes with detailed, self-contained documentation that minimizes startup costs for Zelig and R, automates graphics and summaries for all models, and, with only three simple commands required, generally makes the power of R accessible for all users. Zelig also works well for teaching, and is designed so that scholars can use the same program they use for their research.

The package is enhanced by the following packages: r-cran-vgam
r-cran-zoo
GNU R package for totally ordered indexed observations
Maintainer: Dirk Eddelbuettel
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This package contains an S4 class with methods for totally ordered indexed observations such as irregular time series.

r-recommended
GNU R collection of recommended packages [metapackage]
Maintainer: Dirk Eddelbuettel
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R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files.

The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme.

The core of R is an interpreted computer language which allows branching and looping as well as modular programming using functions. Most of the user-visible functions in R are written in R. It is possible for the user to interface to procedures written in the C, C++, or FORTRAN languages for efficiency, and many of R's core functions do so. The R distribution contains functionality for a large number of statistical procedures and underlying applied math computations. There is also a large set of functions which provide a flexible graphical environment for creating various kinds of data presentations.

Additionally, several thousand extension "packages" are available from CRAN, the Comprehensive R Archive Network, many also as Debian packages, named 'r-cran-'.

This Debian package is now a metapackage that depends on a set of packages that are recommended by the upstream R core team as part of a complete R distribution, and distributed along with the source of R itself, as well as directly via the CRAN network of mirrors. This set comprises the following packages (listed in their upstream names):

  • KernSmooth: Functions for kernel smoothing for Wand & Jones (1995)
  • Matrix: Classes and methods for dense and sparse matrices and operations on them using Lapack and SuiteSparse
  • MASS, class, nnet and spatial: packages from Venables and Ripley, `Modern Applied Statistics with S' (4th edition).
  • boot: Bootstrap R (S-Plus) Functions from the book "Bootstrap Methods and Their Applications" by A.C. Davison and D.V. Hinkley (1997).
  • cluster: Functions for clustering (by Rousseeuw et al.)
  • codetools: Code analysis tools for R
  • foreign: Read data stored by Minitab, S, SAS, SPSS, Stata, ...
  • lattice: Implementation of Trellis (R) graphics
  • mgcv: Multiple smoothing parameter estimation and GAMs by GCV
  • nlme: Linear and nonlinear mixed effects models
  • rpart: Recursive partitioning and regression trees
  • survival: Survival analysis, including penalised likelihood.
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rkward
KDE frontend to the R statistics language
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RKWard aims to become an easy to use, transparent frontend to R, a powerful system for statistical computation and graphics. Besides a convenient GUI for the most important statistical functions, future versions will also provide seamless integration with an office-suite.

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libapophenia2-dev
Apophenia Statistical C Library -- development package
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The Apophenia Statistical C Library is an open source C library for working with data sets and statistical models. It provides functions on the same level as those of the typical stats packages (such as OLS, probit, or singular value decomposition) but gives the user more flexibility to be creative in model-building.

Apophenia is meant to scale well, to comfortably work with gigabyte data sets, million-step simulations, or computationally-intensive agent-based models.

Apophenia builds upon the GNU Scientific and SQLite libraries, MySQL/mariaDB is also supported. The core functions are written in C, but experience has shown them to be easy to bind in Python, Julia, Perl, Ruby, etc. The source code is distributed under the GNU General Public License version 2 (GPL2).

This package contains the header files, static libraries and symbolic links that developers using the Apophenia Statistical C Library will need.

libicb-utils-java
Java library of utilities to manage files and compute statistics
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icb-utils is a group of tools originally designed by the Campagne laboratory for computational biomedicine software. They include extensions of standard Java to manage io, extended iterator classes, hashtables, network-related classes, as well as a set of classes allowing for the computation of statistics.

libtamuanova-dev
Development files for the TAMU ANOVA library
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C library for single and two factor ANOVA.

This package contains the header and development files for the tamuanova library.

node-shiny-server-client
browser library for connecting to Shiny Server
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This Node.js package provides unified client code for Shiny Server, Shiny Server Pro, and RStudio Connect. Previously, each server product had its own version of this code with slight differences. This package provides the superset of functionality needed by the different products, and runtime options determine what features to enable.

Node.js is an event-based server-side JavaScript engine.

python3-leidenalg
Python3 implementation of the Leiden algorithm in C++
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This package implements the Leiden algorithm in C++ and exposes it to Python. It relies on igraph for it to function. Besides the relative flexibility of the implementation, it also scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The core function is find_partition which finds the optimal partition using the Leiden algorithm, which is an extension of the Louvain algorithm for a number of different methods. The methods currently implemented are

 1. modularity,
 2. Reichardt and Bornholdt's model using the configuration null model
    and the Erdös-Rényi null model,
 3. the Constant Potts model (CPM),
 4. Significance and finally
 5. Surprise.

In addition, it supports multiplex partition optimisation allowing community detection on for example negative links or multiple time slices. There is the possibility of only partially optimising a partition, so that some community assignments remain fixed. It also provides some support for community detection on bipartite graphs.

Please cite: V. A. Traag, L. Waltman and N.-J. Van Eck: From Louvain to Leiden: guaranteeing well-connected communities. (eprint) Scientific reports 9(1):5233 (2018)
python3-pynndescent
nearest neighbor descent for approximate nearest neighbors
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PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors. It provides a Python implementation of Nearest Neighbor Descent for k-neighbor-graph construction and approximate nearest neighbor search, as per the paper:

Dong, Wei, Charikar Moses, and Kai Li. "Efficient k-nearest neighbor graph construction for generic similarity measures." Proceedings of the 20th international conference on World wide web. ACM, 2011.

This library supplements that approach with the use of random projection trees for initialisation. This can be particularly useful for the metrics that are amenable to such approaches (euclidean, minkowski, angular, cosine, etc.). Graph diversification is also performed, pruning the longest edges of any triangles in the graph.

Currently this library targets relatively high accuracy (80%-100% accuracy rate) approximate nearest neighbor searches.

r-cran-bbmle
GNU R tools for general maximum likelihood estimation
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This GNU R package provides methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.

r-cran-blockmodeling
Generalized and classical blockmodeling of valued networks
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This R package is primarly meant as an implementation of Generalized blockmodeling for valued networks. In addition, measurese of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithm) can be computed and partitioned matrices can be ploted.

Please cite: Aleš Žiberna: Blockmodeling of multilevel networks. (eprint) Social Networks 39:46 - 61 (2014)
r-cran-brglm
GNU R package for bias reduction in binomial-response GLMs
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Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.

r-cran-catools
GNU R package providing various utility functions
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The packages features several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off error free sum and cumsum, etc.

This package of R programming tools for plotting data was written by Jarek Tuszynski.

r-cran-ellipse
GNU R functions for drawing ellipses and ellipse-like confidence regions
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This package contains various routines for drawing ellipses and ellipse- like confidence regions, implementing the plots described in Murdoch and Chow (1996). There are also routines implementing the profile plots described in Bates and Watts (1988), Nonlinear Regression Analysis and its Applications.

Please cite: D. J. Murdocha and E. D. Chowa: A Graphical Display of Large Correlation Matrices. The American Statistician 50(2):178-180 (1996)
r-cran-fastmatch
GNU R package for fast match replacement for repeated look-ups
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This R package provides a fast match replacement for cases that require repeated look-ups. Extremely fast after the first lookup match as it keeps the hash table in memory.

r-cran-futile.logger
logging utility for GNU R
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This GNU R package provides a simple yet powerful logging utility. Based loosely on log4j, futile.logger takes advantage of R idioms to make logging a convenient and easy to use replacement for cat and print statements.

r-cran-futile.options
GNU R futile options management
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This GNU R package provides a scoped options management framework.

r-cran-gnm
GNU R package for generalized nonlinear models
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Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science, and many others. Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.

r-cran-igraph
GNU R network analysis and visualization
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This GNU R package provides routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more.

r-cran-irlba
GNU R fast truncated SVD, PCA and symmetric eigendecomposition
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This GNU R package provides Fast and memory efficient methods for truncated singular and eigenvalue decompositions and principal component analysis of large sparse or dense matrices.

r-cran-lambda.r
GNU R modeling data with functional programming
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This GNU R package provides a language extension to efficiently write functional programs in R. Syntax extensions include multi-part function definitions, pattern matching, guard statements, built-in (optional) type safety.

r-cran-luminescence
GNU R comprehensive luminescence dating data analysis
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A collection of various R functions for the purpose of Luminescence dating data analysis. This includes, amongst others, data import, export, application of age models, curve deconvolution, sequence analysis and plotting of equivalent dose distributions.

r-cran-magrittr
GNU R forward-pipe operator
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Provides a mechanism for chaining commands with a new forward-pipe operator, %>%. This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions.

r-cran-minpack.lm
GNU R Levenberg-Marquardt nonlinear least-squares algorithm found in MINPACK
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The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds. The implementation can be used via nls- like calls using the nlsLM function.

r-cran-mlmrev
GNU R Examples from Multilevel Modelling Software Review
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This GNU R package provides data and examples from a multilevel modelling software review as well as other well-known data sets from the multilevel modelling literature.

r-cran-nnls
GNU R package for non-negative least squares (the Lawson-Hanson algorithm)
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An R package to the Lawson-Hanson implementation of an algorithm for non- negative least squares (NNLS). Also allows the combination of non-negative and non-positive constraints.

r-cran-princurve
fit a principal curve in arbitrary dimension
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GNU R package to fit a principal curve to a data matrix in arbitrary dimensions.

r-cran-r.oo
GNU R object-oriented programming with or without references
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Methods and classes for object-oriented programming in R with or without references. Large effort has been made on making definition of methods as simple as possible with a minimum of maintenance for package developers. The package has been developed since 2001 and is now considered very stable. This is a cross-platform package implemented in pure R that defines standard S3 classes without any tricks.

Please cite: Henrik Bengtsson: The R.oo package - Object-Oriented Programming with References Using Standard R Code. (eprint) Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003) (2003)
r-cran-r.utils
GNU R various programming utilities
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This GNU R package contains various programming utilities, These functions are useful when programming and developing R packages.

r-cran-rngtools
GNU R package for random number generators
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This package contains a set of functions for working with Random Number Generators (RNGs). In particular, it defines a generic S4 framework for getting/setting the current RNG, or RNG data that are embedded into objects for reproducibility. Notably, convenient default methods greatly facilitate the way current RNG settings can be changed.

r-cran-spc
GNU R Statistical Process Control
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Evaluation of control charts by means of the zero-state, steady-state ARL (Average Run Length). Setting up control charts for given in-control ARL and plotting of the related figures. The control charts under consideration are one- and two-sided EWMA and CUSUM charts for monitoring the mean of normally distributed independent data. Now, the ARL calculation of EWMA-S^2 control charts is added. Other charts and parameters are in preparation. Further SPC areas will be covered as well (sampling plans, capability indices ...).

science-mathematics
Науковий набір Debian — пакунки з математики
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Debtags of package science-mathematics:
fieldmathematics
rolemetapackage
suitedebian
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Цей збірний пакунок встановить усі пакунки з Наукового набору Debian, що стосуються математики. Вас також зацікавить поле field::mathematics у debtag, а також, в залежності від ваших уподобань, пакунки на які посилається збірний пакунок education-mathematics.

Packaging has started and developers might try the packaging code in VCS

rstudio
GNU R IDE
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Version: 2022.07.1+554-1

RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.

Unofficial packages built by somebody else

r-cran-fcalendar
GNU R package for financial engineering -- fCalendar
License: unknown

This package of functions for financial engineering and computational finance is part of Rmetrics, a collection of packages written and compiled by Diethelm Wuertz.

fCalendar provides basic time and date manipulations, holiday calculators and other tools. Its code was previously provided within the fBasics package from which it has been split off.

Remark of Debian Science team: Removed from Debian

This package was removed from Debian but some versions are available from http://snapshot.debian.org/

Reasons are given here: http://bugs.debian.org/554513

*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 237410