Summary
Epidemiology
이 메타패키지는 역학 연구에 유용한 도구를 설치할 것 입니다. 통계 조사를 위해 GNU R 데이타 언어를 사용하는 여러 패키지들. "A short introduction to R for
Epidemiology (역학을 위한 R에 대한 간략한 소개)" 논문을 http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf 에서 읽어보는 것이 좋습니다.
Description
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If you discover a project which looks like a good candidate for Debian Med
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Links to other tasks
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Debian Med Epidemiology packages
Official Debian packages with high relevance
python3-seirsplus
Models of SEIRS epidemic dynamics with extensions
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Versions of package python3-seirsplus |
Release | Version | Architectures |
bookworm | 1.0.9-1 | all |
trixie | 1.0.9-2 | all |
bullseye | 0.1.4+git20200528.5c04080+ds-2 | all |
sid | 1.0.9-2 | all |
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License: DFSG free
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This package implements generalized SEIRS infectious disease
dynamics models with extensions that model the effect of factors
including population structure, social distancing, testing, contact
tracing, and quarantining detected cases.
Notably, this package includes stochastic implementations of these
models on dynamic networks.
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python3-torch
Tensors and Dynamic neural networks in Python (Python Interface)
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Versions of package python3-torch |
Release | Version | Architectures |
bookworm | 1.13.1+dfsg-4 | amd64,arm64,ppc64el,s390x |
bullseye | 1.7.1-7 | amd64,arm64,armhf,ppc64el,s390x |
sid | 2.5.0+dfsg-1 | amd64,arm64,ppc64el,riscv64,s390x |
upstream | 2.5.1 |
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License: DFSG free
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PyTorch is a Python package that provides two high-level features:
(1) Tensor computation (like NumPy) with strong GPU acceleration
(2) Deep neural networks built on a tape-based autograd system
You can reuse your favorite Python packages such as NumPy, SciPy and Cython
to extend PyTorch when needed.
This is the CPU-only version of PyTorch (Python interface).
Please cite:
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai and Soumith Chintala:
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python3-treetime
inference of time stamped phylogenies and ancestral reconstruction (Python 3)
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Versions of package python3-treetime |
Release | Version | Architectures |
buster | 0.5.3-1 | all |
bullseye | 0.8.1-1 | all |
sid | 0.11.1-1 | all |
trixie | 0.11.1-1 | all |
bookworm | 0.9.4-1 | all |
upstream | 0.11.4 |
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License: DFSG free
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TreeTime provides routines for ancestral sequence reconstruction and the
maximum likelihoo inference of molecular-clock phylogenies, i.e., a tree
where all branches are scaled such that the locations of terminal nodes
correspond to their sampling times and internal nodes are placed at the
most likely time of divergence.
TreeTime aims at striking a compromise between sophisticated
probabilistic models of evolution and fast heuristics. It implements GTR
models of ancestral inference and branch length optimization, but takes
the tree topology as given. To optimize the likelihood of time-scaled
phylogenies, treetime uses an iterative approach that first infers
ancestral sequences given the branch length of the tree, then optimizes
the positions of unconstraine d nodes on the time axis, and then repeats
this cycle. The only topology optimization are (optional) resolution of
polytomies in a way that is most (approximately) consistent with the
sampling time constraints on the tree. The package is designed to be
used as a stand-alone tool or as a library used in larger phylogenetic
analysis workflows.
Features
- ancestral sequence reconstruction (marginal and joint maximum
likelihood)
- molecular clock tree inference (marginal and joint maximum
likelihood)
- inference of GTR models
- rerooting to obtain best root-to-tip regression
- auto-correlated relaxed molecular clock (with normal prior)
This package provides the Python 3 module.
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r-cran-covid19us
cases of COVID-19 in the United States prepared for GNU R
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Versions of package r-cran-covid19us |
Release | Version | Architectures |
trixie | 0.1.9-1 | all |
bookworm | 0.1.9-1 | all |
bullseye | 0.1.7-1 | all |
sid | 0.1.9-1 | all |
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License: DFSG free
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This package provides a GNU R wrapper around the 'COVID Tracking Project API'
https://covidtracking.com/api/ providing data on cases of COVID-19
in the US.
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r-cran-diagnosismed
medical diagnostic test accuracy analysis toolkit
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Versions of package r-cran-diagnosismed |
Release | Version | Architectures |
bookworm | 0.2.3-7 | all |
bullseye | 0.2.3-7 | all |
stretch | 0.2.3-4 | all |
trixie | 0.2.3-7 | all |
sid | 0.2.3-7 | all |
buster | 0.2.3-6 | all |
jessie | 0.2.3-3 | all |
Debtags of package r-cran-diagnosismed: |
devel | lang:r |
field | medicine |
interface | commandline |
role | program |
use | analysing |
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License: DFSG free
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DiagnosisMed is a GNU R package to analyze the accuracy of data from
diagnostic tests evaluating health conditions. It was designed to be
used by health professionals. This package helps estimating sensitivity
and specificity from categorical and continuous test results including
some evaluations of indeterminate results, or compare different
categorical tests, and estimate reasonable cut-offs of tests and display
it in a way commonly used by health professionals. No graphical
interface is available yet.
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r-cran-epi
GNU R epidemiological analysis
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Versions of package r-cran-epi |
Release | Version | Architectures |
buster | 2.32-2 | amd64,arm64,armhf,i386 |
bullseye | 2.43-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.47-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
jessie | 1.1.67-4 | amd64,armel,armhf,i386 |
stretch | 2.7-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 2.56 |
Debtags of package r-cran-epi: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Functions for demographic and epidemiological analysis in the Lexis diagram,
i.e. register and cohort follow-up data, including interval censored data and
representation of multistate data. Also some useful functions for tabulation
and plotting. Contains some epidemiological datasets.
The Epi package is mainly focused on "classical" chronic disease epidemiology.
The package has grown out of the course Statistical Practice in Epidemiology
using R (see http://www.pubhealth.ku.dk/~bxc/SPE).
There is A short introduction to R for Epidemiology available at
http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf
Beware that the pages 38-120 of this is merely the manual pages for the Epi
package.
Epi is not the only R-package for epidemiological analysis, a package with
more affinity to infectious disease epidemiology is the epitools package
which is also evailable in Debian.
Epi is used in the Department of Biostatistics of the University of Copenhagen.
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r-cran-epibasix
GNU R Elementary Epidemiological Functions
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Versions of package r-cran-epibasix |
Release | Version | Architectures |
bullseye | 1.5-2 | all |
stretch | 1.3-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.3-1 | amd64,armel,armhf,i386 |
buster | 1.5-1 | all |
sid | 1.5-2 | all |
trixie | 1.5-2 | all |
bookworm | 1.5-2 | all |
Debtags of package r-cran-epibasix: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Elementary Epidemiological Functions for a Graduate Epidemiology /
Biostatistics Course.
This package contains elementary tools for analysis of common epidemiological
problems, ranging from sample size estimation, through 2x2 contingency table
analysis and basic measures of agreement (kappa, sensitivity/specificity).
Appropriate print and summary statements are also written to facilitate
interpretation wherever possible. This package is a work in progress, so
any comments or suggestions would be appreciated. Source code is commented
throughout to facilitate modification. The target audience includes graduate
students in various epi/biostatistics courses.
Epibasix was developed in Canada.
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r-cran-epicalc
GNU R Epidemiological calculator
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Versions of package r-cran-epicalc |
Release | Version | Architectures |
bookworm | 2.15.1.0-5 | all |
sid | 2.15.1.0-5 | all |
trixie | 2.15.1.0-5 | all |
bullseye | 2.15.1.0-5 | all |
buster | 2.15.1.0-4 | all |
stretch | 2.15.1.0-2 | all |
jessie | 2.15.1.0-1 | all |
Debtags of package r-cran-epicalc: |
devel | lang:r |
field | medicine, statistics |
interface | commandline |
role | program |
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License: DFSG free
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Functions making R easy for epidemiological calculation.
Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and
Comma separated value (.csv) formats as well as R data frames can be
processed to do make several epidemiological calculations.
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r-cran-epiestim
GNU R estimate time varying reproduction numbers from rpidemic curves
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Versions of package r-cran-epiestim |
Release | Version | Architectures |
bookworm | 2.2-4+dfsg-1 | all |
trixie | 2.2-4+dfsg-1 | all |
sid | 2.2-4+dfsg-1 | all |
buster-backports | 2.2-4+dfsg-1~bpo10+1 | all |
bullseye | 2.2-4+dfsg-1 | all |
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License: DFSG free
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Tools to quantify transmissibility throughout
an epidemic from the analysis of time series of incidence as described in
Cori et al. (2013) and Wallinga and Teunis (2004)
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r-cran-epir
GNU R Functions for analysing epidemiological data
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Versions of package r-cran-epir |
Release | Version | Architectures |
jessie | 0.9-59-1 | all |
stretch | 0.9-79-1 | all |
buster | 0.9-99-1 | all |
bullseye | 2.0.19-1 | all |
bookworm | 2.0.57+dfsg-1 | all |
sid | 2.0.76+dfsg-1 | all |
Debtags of package r-cran-epir: |
devel | lang:r |
field | medicine |
interface | commandline |
role | program |
use | analysing |
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License: DFSG free
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A package for analysing epidemiological data. Contains functions for
directly and indirectly adjusting measures of disease frequency,
quantifying measures of association on the basis of single or multiple
strata of count data presented in a contingency table, and computing
confidence intervals around incidence risk and incidence rate estimates.
Miscellaneous functions for use in meta-analysis, diagnostic test
interpretation, and sample size calculations.
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r-cran-epitools
GNU R Epidemiology Tools for Data and Graphics
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Versions of package r-cran-epitools |
Release | Version | Architectures |
bookworm | 0.5-10.1-2 | all |
trixie | 0.5-10.1-2 | all |
sid | 0.5-10.1-2 | all |
jessie | 0.5-7-1 | all |
stretch | 0.5-7-1 | all |
buster | 0.5-10-2 | all |
bullseye | 0.5-10.1-2 | all |
Debtags of package r-cran-epitools: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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GNU R Tools for public health epidemiologists and data analysts.
Epitools provides numerical tools and programming solutions that
have been used and tested in real-world epidemiologic applications.
Many practical problems in the analysis of public health data
require programming or special software, and investigators in
different locations may duplicate programming efforts. Often,
simple analyses, such as the construction of confidence intervals,
are not calculated and thereby complicate appropriate statistical
inferences for small geographic areas. There are many examples of
simple and useful numerical tools that would enhance the work of
epidemiologists at local health departments and yet are not readily
available for the problem in front of them. The availability of
these tools will encourage wider use of appropriate methods and
promote evidence-based public health practices.
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r-cran-incidence
GNU R compute, handle, plot and model incidence of dated events
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Versions of package r-cran-incidence |
Release | Version | Architectures |
bookworm | 1.7.3-1 | all |
trixie | 1.7.5-1 | all |
sid | 1.7.5-1 | all |
bullseye | 1.7.3-1 | all |
buster-backports | 1.7.3-1~bpo10+1 | all |
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License: DFSG free
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Provides functions and classes to compute, handle and visualise
incidence from dated events for a defined time interval. Dates can be
provided in various standard formats. The class 'incidence' is used to
store computed incidence and can be easily manipulated, subsetted, and
plotted. In addition, log-linear models can be fitted to 'incidence'
objects using 'fit'. This package is part of the RECON
(http://www.repidemicsconsortium.org/) toolkit for outbreak analysis.
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r-cran-kernelheaping
GNU R kernel density estimation for heaped and rounded data
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Versions of package r-cran-kernelheaping |
Release | Version | Architectures |
sid | 2.3.0-1 | all |
bookworm | 2.3.0-1 | all |
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License: DFSG free
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In self-reported or anonymised data the user often encounters heaped
data, i.e. data which are rounded (to a possibly different degree of
coarseness). While this is mostly a minor problem in parametric density
estimation the bias can be very large for non-parametric methods such as
kernel density estimation. This package implements a partly Bayesian
algorithm treating the true unknown values as additional parameters and
estimates the rounding parameters to give a corrected kernel density
estimate. It supports various standard bandwidth selection methods.
Varying rounding probabilities (depending on the true value) and
asymmetric rounding is estimable as well: Gross, M. and Rendtel, U.
(2016) (). Additionally, bivariate non-
parametric density estimation for rounded data, Gross, M. et al. (2016)
(), as well as data aggregated on areas is
supported.
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r-cran-lexrankr
extractive summarization of text with the LexRank algorithm
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Versions of package r-cran-lexrankr |
Release | Version | Architectures |
sid | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.5.0-2 | amd64,arm64,armhf,i386 |
bullseye | 0.5.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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An R implementation of the LexRank algorithm implementing stochastic
graph-based method for computing relative importance of textual units
for Natural Language Processing. The technique on the problem
of Text Summarization (TS) is tested. Extractive TS relies on the concept of
sentence salience to identify the most important sentences in a
document or set of documents. Salience is typically defined in terms of
the presence of particular important words or in terms of similarity to
a centroid pseudo-sentence.
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r-cran-prevalence
GNU R tools for prevalence assessment studies
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Versions of package r-cran-prevalence |
Release | Version | Architectures |
sid | 0.4.1-1 | all |
bookworm | 0.4.1-1 | all |
trixie | 0.4.1-1 | all |
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License: DFSG free
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The prevalence package provides Frequentist and Bayesian methods for
prevalence assessment studies. IMPORTANT: the truePrev functions in the
prevalence package call on JAGS (Just Another Gibbs Sampler), which
therefore has to be available on the user's system. JAGS can be
downloaded from http://mcmc-jags.sourceforge.net/.
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r-cran-seroincidence
GNU R seroincidence calculator tool
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Versions of package r-cran-seroincidence |
Release | Version | Architectures |
stretch | 1.0.5-1 | all |
bullseye | 2.0.0-2 | all |
buster | 2.0.0-1 | all |
sid | 2.0.0-3 | all |
trixie | 2.0.0-3 | all |
bookworm | 2.0.0-3 | all |
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License: DFSG free
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Antibody levels measured in a cross-sectional population samples can be
translated into an estimate of the frequency with which seroconversions
(new infections) occur. In order to interpret the measured
cross-sectional antibody levels, parameters which predict the decay of
antibodies must be known. In previously published reports (Simonsen et
al. 2009 and Versteegh et al. 2005), this information has been obtained
from longitudinal studies on subjects who had culture-confirmed
Salmonella and Campylobacter infections. A Bayesian back-calculation
model was used to convert antibody measurements into an estimation of
time since infection. This can be used to estimate the seroincidence in
the cross-sectional sample of population. For both the longitudinal and
cross-sectional measurements of antibody concentrations, the indirect
ELISA was used. The models are only valid for persons over 18 years. The
seroincidence estimates are suitable for monitoring the effect of
control programmes when representative cross-sectional serum samples are
available for analyses. These provide more accurate information on the
infection pressure in humans across countries.
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r-cran-sf
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Versions of package r-cran-sf |
Release | Version | Architectures |
bookworm | 1.0-9+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.9-7+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0-17+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 0.6-3+dfsg-1~bpo9+1 | arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
stretch-backports | 0.7-2+dfsg-1~bpo9+1 | amd64 |
buster | 0.7-2+dfsg-1 | amd64,arm64,armhf,i386 |
upstream | 1.0-19 |
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License: DFSG free
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Support for simple features, a standardized way to encode spatial vector
data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for
geometrical operations, and to 'PROJ' for projection conversions and
datum transformations.
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r-cran-sjplot
GNU R data visualization for statistics in social science
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Versions of package r-cran-sjplot |
Release | Version | Architectures |
bullseye | 2.8.7-1 | all |
stretch-backports | 2.6.2-1~bpo9+1 | all |
buster | 2.6.2-1 | all |
bookworm | 2.8.12+dfsg-1 | all |
sid | 2.8.16+dfsg-1 | all |
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License: DFSG free
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Collection of plotting and table output functions for data
visualization. Results of various statistical analyses (that are
commonly used in social sciences) can be visualized using this package,
including simple and cross tabulated frequencies, histograms, box plots,
(generalized) linear models, mixed effects models, principal component
analysis and correlation matrices, cluster analyses, scatter plots,
stacked scales, effects plots of regression models (including
interaction terms) and much more. This package supports labelled data.
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r-cran-surveillance
전염병 현상의 모델링 및 모니터링을 위한 GNU R 패키지
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Versions of package r-cran-surveillance |
Release | Version | Architectures |
jessie | 1.8-0-1 | amd64,armel,armhf,i386 |
bookworm | 1.20.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.19.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.16.2-1 | amd64,arm64,armhf,i386 |
stretch | 1.13.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 1.24.1 |
Debtags of package r-cran-surveillance: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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전염병 형상의 연속 지점 프로세스 모델링뿐만 아니라, 시계열 갯수, 비율 및 범주형 데이터의 모델링 및 모니터링을 위한 통계적 방법.
모니터링 방법은 전염병에 대한 공중 보건 감시의 카운트 데이터 시계열에서 이상 감지에 중점을 두지만 어플리케이션은 환경 측정, 신뢰성 공학, 계량 경제학 또는 사회 과학에서 유래할 수도 있습니다. 패키지는 (개선된) Farrington 알고리즘이나 Höhle 및 Paul(2008) 의 음이항 GLR-CUSUM 방법과 같은 많은 일반적인 발병 감지 절차를 구현합니다. 로지스틱과 다항 로지스틱 모델링을 결합한 새로운 CUSUM 접근 방식도 포함되어 있습니다. 패키지에는 여러 실제 데이터 세트, 발병 데이터를 시뮬레이션하는 기능, 시간적, 공간적 또는 시공간적 방식으로 모니터링 결과를 시각화하는 기능이 포함되어 있습니다. 이용 가능한 모니터링 절차에 대한 최근의 개요는 Salmon et al. (2016) 에 의해 제공됩니다.
전염병 확산에 대한 회고적 분석을 위해 패키지는 시각화, 가능성 추론 및 시뮬레이션을 위한 도구가 포함된 세 가지 풍토병-전염병 모델링 프레임워크를 제공합니다. hhh4()는 Paul and Held(2011) 및 Meyer and Held(2014) 에 따라 (다변량) 카운트 시계열에 대한 모델을 추정합니다. TwinSIR()은 Höhle(2009) 이 제안한 다변량 포인트 프로세스로 농장이나 네트워크 전반에 걸친 전염병과 같은 고정 인구의 SIR(감수성 감염 복구) 이벤트 기록을 모델링합니다. Twinstim()은 Meyer 등이 제안한 것처럼 감염성 이벤트의 시공간 포인트 패턴(예: 타임스탬프가 지정된 지리 참조 감시 데이터)에 대한 자기 흥분점포인트 프로세스 모델을 추정합니다. (2012) . 전염병 현상에 대해 구현된 시공간 모델링 프레임워크에 대한 최근 개요는 Meyer et al. (2017) 에 의해서 제공됩니다.
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Official Debian packages with lower relevance
python3-epimodels
simple interface to simulate mathematical epidemic models in Python3
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Versions of package python3-epimodels |
Release | Version | Architectures |
bookworm | 0.4.0-1 | all |
sid | 0.4.0-4 | all |
trixie | 0.4.0-4 | all |
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License: DFSG free
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This library provides a simple interface to simulate mathematical
epidemic models in Python3. It is a precondition for the program
epigrass.
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r-cran-cmprsk
GNU R subdistribution analysis of competing risks
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Versions of package r-cran-cmprsk |
Release | Version | Architectures |
trixie | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.2-7-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.2-7-4 | amd64,arm64,armhf,i386 |
bullseye | 2.2-10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.2-12 |
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License: DFSG free
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This GNU R package supports estimation, testing and regression modeling
of subdistribution functions in competing risks, as described in Gray
(1988), A class of K-sample tests for comparing the cumulative incidence
of a competing risk.
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r-cran-msm
지속 시간에서 GNU R 다중 상태 마르코프 및 은닉 마르코프 모델
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Versions of package r-cran-msm |
Release | Version | Architectures |
sid | 1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 1.6.4-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.4-2 | amd64,armel,armhf,i386 |
bullseye | 1.6.8-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.6.6-2 | amd64,arm64,armhf,i386 |
upstream | 1.8.2 |
Debtags of package r-cran-msm: |
interface | commandline |
role | program |
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License: DFSG free
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일반적인 지속 시간 마르코프 및 은닉 마르코프 다중 상태 모델을 종단 데이타에
맞추기 위한 함수. 마르코프 전이 속도와 은닉 마르코프 출력 프로세스는 공변
측면에서 모델링 될 수 있습니다. 임의의 시간에 관측된 프로세스, 완전히 관측
된 프로세스, 검열 상태등을 포함해서 다양한 관측 스키마가 지원됩니다.
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shiny-server
put Shiny web apps online
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Versions of package shiny-server |
Release | Version | Architectures |
bookworm | 1.5.20.1002-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.5.20.1002-3 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 1.5.23.1030 |
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License: DFSG free
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Shiny Server lets you put shiny web applications and interactive
documents online. Take your Shiny apps and share them with your
organization or the world.
Shiny Server lets you go beyond static charts, and lets you manipulate
the data. Users can sort, filter, or change assumptions in real-time.
Shiny server empower your users to customize your analysis for their
specific needs and extract more insight from the data.
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Packaging has started and developers might try the packaging code in VCS
chime
COVID-19 Hospital Impact Model for Epidemics
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Versions of package chime |
Release | Version | Architectures |
VCS | 0.2.1-1 | all |
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License: MIT
Debian package not available
Version: 0.2.1-1
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Penn Medicine - COVID-19 Hospital Impact Model for Epidemics
This tool was developed by the Predictive Healthcare team at Penn
Medicine. For questions and comments please see our contact page. Code
can be found on Github. Join our Slack channel if you would like to
get involved!
The estimated number of currently infected individuals is 533. The 91
confirmed cases in the region imply a 17% rate of detection. This is
based on current inputs for Hospitalizations (4), Hospitalization rate
(5%), Region size (4119405), and Hospital market share (15%).
An initial doubling time of 6 days and a recovery time of 14.0 days
imply an R_0 of 2.71.
Mitigation: A 0% reduction in social contact after the onset of the
outbreak reduces the doubling time to 6.0 days, implying an effective
R_t of 2.712.712.71.
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epifire
model the spread of an infectious disease in a population
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Versions of package epifire |
Release | Version | Architectures |
VCS | 3.34.0+dfsg-1 | all |
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License: BSD-3-clause
Debian package not available
Version: 3.34.0+dfsg-1
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EpiFire is a C++ applications programming interface (API) that does
two things:
- Model the spread of an infectious disease in a population
- Generate and manipulate networks of nodes and edges
While the network code can be used independently from the
epidemiological code and vice versa—they are conceptually and
functionally distinct—from the beginning, the libraries were developed
to be compatible with each other. What EpiFire excels at is simulating
the stochastic spread of disease on contact networks.
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netepi-analysis
network-enabled tools for epidemiology and public health practice
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Versions of package netepi-analysis |
Release | Version | Architectures |
VCS | 0.9.0-2 | all |
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License: HACOS
Debian package not available
Version: 0.9.0-2
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NetEpi, which is short for "Network-enabled Epidemiology", is a
collaborative project to create a suite of free, open source software
tools for epidemiology and public health practice. Anyone with an
interest in population health epidemiology or public health
informatics is encouraged to examine the prototype tools and to
consider contributing to their further development. Contributions
which involve formal and/or informal testing of the tools in a wide
range of circumstances and environments are particularly welcome, as
is assistance with design, programming and documentation tasks.
This is a tool for conducting epidemiological analysis of data sets,
both large and small, either through a Web browser interface, or via
a programmatic interface. In many respects it is similar to the
analysis facilities included in the Epi Info suite, except that
NetEpi Analysis is designed to be installed on servers and accessed
remotely via Web browsers, although it can also be installed on
individual desktop or laptop computers.
The software was developed by New South Wales Department of Health.
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netepi-collection
network-enabled tools for epidemiology and public health practice
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Versions of package netepi-collection |
Release | Version | Architectures |
VCS | 1.8.4-2 | all |
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License: HACOS
Debian package not available
Version: 1.8.4-2
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NetEpi, which is short for "Network-enabled Epidemiology", is a
collaborative project to create a suite of free, open source software
tools for epidemiology and public health practice. Anyone with an
interest in population health epidemiology or public health
informatics is encouraged to examine the prototype tools and to
consider contributing to their further development. Contributions
which involve formal and/or informal testing of the tools in a wide
range of circumstances and environments are particularly welcome, as
is assistance with design, programming and documentation tasks.
NetEpi Case Manager is a tool for securely collecting structured
information about cases and contacts of communicable (and other)
diseases through Web browsers and the Internet. New data collection
forms can be designed and deployed quickly by epidemiologists, using
a "point-and-click" interface, without the need for knowledge of or
training in any programming language. Data can then be collected from
users of the system, who can be located anywhere in the world, into a
centralised database. All that is needed by users of the system is a
relatively recent Web browser and an Internet connection ("NetEpi" is
short for "Network-enabled Epidemiology"). In many respects, NetEpi
Case Manager is like a Web-enabled version of the data entry
facilities in the very popular Epi Info suite of programmes published
by the US Centers for Disease Control and Prevention, and in the
Danish EpiData project, which is available for several languages. The
software was developed by the Centre for Epidemiology and Research of
the New South Wales Department of Health, with contributions from
Population Health Division of the Australian Government Department of
Health and Ageing.
The software was developed by New South Wales Department of Health.
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r-cran-covid19
GNU R Coronavirus COVID-19 data acquisition and visualization
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Versions of package r-cran-covid19 |
Release | Version | Architectures |
VCS | 0.2.1-1 | all |
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License: GPL-3
Debian package not available
Version: 0.2.1-1
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This GNU R package provides pre-processed, ready-to-use, tidy format
datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. The
latest data are downloaded in real-time, processed and merged with
demographic indicators from several trusted sources. The package
implements advanced data visualization across the space and time
dimensions by means of animated mapping. Besides worldwide data,
the package includes granular data for Italy, Switzerland and the
Diamond Princess.
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ushahidi
web platform for information collection
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Versions of package ushahidi |
Release | Version | Architectures |
VCS | 2.7.4-1 | all |
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License: LGPL-3+
Debian package not available
Version: 2.7.4-1
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Ushahidi is a platform that allows information collection,
visualization and interactive mapping, allowing anyone to submit
information through text messaging using a mobile phone, email or web
form.
It can be used to monitor epidemic diseases, measuring the impact of
natural disasters, uncovering corruption, and empowering peace makers.
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No known packages available but some record of interest (WNPP bug)
framework for creating agent based simulations
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License: BSD
Debian package not available
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Repast Simphony is a free and open source agent-based modeling toolkit
that simplifies model creation and use. Repast Simphony offers users a
rich variety of features including the following:
- Fluid model component development using any mixture of Java, Groovy,
and flowcharts in each project;
- A pure Java point-and-click model execution environment that includes
built-in results logging and graphing tools as well as automated
connections to a variety of optional external tools including the R
statistics environment, *ORA and Pajek network analysis plugins, A
live agent SQL query tool plugin, the VisAD scientific visualization
package, the Weka data mining platform, many popular spreadsheets,
the MATLAB computational mathematics environment, and the iReport
visual report designer;
- An extremely flexible hierarchically nested definition of space
including the ability to do point-and-click and modeling and
visualization of 2D environments; 3D environments; networks including
full integration with the JUNG network modeling library as well as
Microsoft Excel spreadsheets and UCINET DL file importing; and
geographical spaces including 2D and 3D Geographical Information
Systems (GIS) support;
- A range of data storage "freeze dryers" for model check pointing
and restoration including XML file storage, text file storage, and
database storage;
- A fully concurrent multithreaded discrete event scheduler;
- Libraries for genetic algorithms, neural networks, regression, random
number generation, and specialized mathematics;
- An automated Monte Carlo simulation framework which supports multiple
modes of model results optimization;
- Built-in tools for integrating external models;
- Distributed computing with Terracotta;
- Full object-orientation;
- Optional end-to-end XML simulation
- A point-and-click model deployment system
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