Summary
Statistics
This metapackage will install packages which are helpful to do statistics
with a special focus on tasks in medical care.
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 Med
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 Med mailing list
Links to other tasks
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Debian Med Statistics packages
Official Debian packages with high relevance
r-bioc-edger
Empirical analysis of digital gene expression data in R
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Versions of package r-bioc-edger |
Release | Version | Architectures |
trixie | 4.2.2+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 4.4.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 4.2.2+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
jessie | 3.8.2+dfsg-1 | amd64,armel,armhf,i386 |
bookworm | 3.40.2+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 3.32.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 3.14.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 4.4.1 |
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License: DFSG free
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Bioconductor package for differential expression analysis of whole
transcriptome sequencing (RNA-seq) and digital gene expression
profiles with biological replication. It uses empirical Bayes
estimation and exact tests based on the negative binomial
distribution. It is also useful for differential signal analysis with
other types of genome-scale count data.
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r-bioc-limma
linear models for microarray data
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Versions of package r-bioc-limma |
Release | Version | Architectures |
bullseye | 3.46.0+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 3.38.3+dfsg-1 | amd64,arm64,armhf,i386 |
stretch | 3.30.8+dfsg-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 3.22.1+dfsg-1 | amd64,armel,armhf,i386 |
experimental | 3.62.1+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 3.60.6+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
trixie | 3.60.6+dfsg-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
bookworm | 3.54.1+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 3.62.1 |
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License: DFSG free
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Microarrays are microscopic plates with carefully arranged short DNA
strands and/or chemically prepared surfaces to which other DNA
preferably binds. The amount of DNA binding at different locations of
these chips, typically determined by a fluorescent dye, is to be
interpreted. The technology is typically used with DNA that is derived
from RNA, i.e to determine the activity of a gene and/or its splice
variants. But the technology is also used to determine sequence
variations in genomic DNA.
This Bioconductor package supports the analysis of gene expression
microarray data, especially the use of linear models for analysing
designed experiments and the assessment of differential expression. The
package includes pre-processing capabilities for two-colour spotted
arrays. The differential expression methods apply to all array platforms
and treat Affymetrix, single channel and two channel experiments in a
unified way.
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r-bioc-multtest
Bioconductor resampling-based multiple hypothesis testing
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Versions of package r-bioc-multtest |
Release | Version | Architectures |
bullseye | 2.46.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 2.38.0-1 | amd64,arm64,armhf,i386 |
stretch | 2.30.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.54.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.60.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
sid | 2.60.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
experimental | 2.62.0-1 | amd64,arm64,mips64el,ppc64el,riscv64,s390x |
upstream | 2.62.0 |
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License: DFSG free
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Non-parametric bootstrap and permutation resampling-based multiple
testing procedures (including empirical Bayes methods) for controlling
the family-wise error rate (FWER), generalized family-wise error rate
(gFWER), tail probability of the proportion of false positives (TPPFP),
and false discovery rate (FDR). Several choices of bootstrap-based null
distribution are implemented (centered, centered and scaled,
quantile-transformed). Single-step and step-wise methods are available.
Tests based on a variety of t- and F-statistics (including t-statistics
based on regression parameters from linear and survival models as well
as those based on correlation parameters) are included. When probing
hypotheses with t-statistics, users may also select a potentially faster
null distribution which is multivariate normal with mean zero and
variance covariance matrix derived from the vector influence function.
Results are reported in terms of adjusted p-values, confidence regions
and test statistic cutoffs. The procedures are directly applicable to
identifying differentially expressed genes in DNA microarray
experiments.
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r-bioc-qvalue
GNU R package for Q-value estimation for FDR control
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Versions of package r-bioc-qvalue |
Release | Version | Architectures |
stretch | 2.6.0-1 | all |
buster | 2.14.1-1 | all |
bullseye | 2.22.0-1 | all |
bookworm | 2.30.0-1 | all |
trixie | 2.36.0-1 | all |
sid | 2.36.0-1 | all |
jessie | 1.40.0-1 | all |
experimental | 2.38.0-1 | all |
upstream | 2.38.0 |
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License: DFSG free
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This package takes a list of p-values resulting from the simultaneous
testing of many hypotheses and estimates their q-values. The
q-value of a test measures the proportion of false positives incurred
(called the false discovery rate) when that particular test is called
significant. Various plots are automatically generated, allowing one
to make sensible significance cut-offs. Several mathematical results
have recently been shown on the conservative accuracy of the estimated
q-values from this software. The software can be applied to problems
in genomics, brain imaging, astrophysics, and data mining.
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r-cran-ade4
GNU R analysis of ecological data
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Versions of package r-cran-ade4 |
Release | Version | Architectures |
trixie | 1.7-22-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.7-22-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.7-16-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.7-13-1 | amd64,arm64,armhf,i386 |
stretch | 1.7-5-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 1.7-22-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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This GNU R package allows analysis of ecological data and contains
exploratory and euclidean methods in environmental sciences.
It supports multivariate data analysis and graphical display.
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r-cran-beeswarm
bee swarm plot, an alternative to stripchart
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Versions of package r-cran-beeswarm |
Release | Version | Architectures |
trixie | 0.4.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 0.4.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 0.2.3-1 | all |
jessie | 0.1.6-2 | all |
buster | 0.2.3-3 | all |
bullseye | 0.2.3-4 | all |
bookworm | 0.4.0-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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Beeswarm is an add-on package for the R statistical environment. The bee swarm
plot is a one-dimensional scatter plot like "stripchart", but with
closely-packed, non-overlapping points.
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r-cran-pvclust
Hierarchical Clustering with P-Values via Multiscale Bootstrap
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Versions of package r-cran-pvclust |
Release | Version | Architectures |
stretch | 2.0-0-1 | all |
jessie | 1.3-0-1 | all |
buster | 2.0-0-4 | all |
bullseye | 2.2-0-2 | all |
bookworm | 2.2-0-2 | all |
trixie | 2.2-0-2 | all |
sid | 2.2-0-2 | all |
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License: DFSG free
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pvclust is a package for assessing the uncertainty in
hierarchical cluster analysis. It provides AU (approximately
unbiased) p-values as well as BP (boostrap probability) values
computed via multiscale bootstrap resampling.
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r-cran-randomforest
Pakiet GNU R implementujący klasyfikator lasów losowych
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Versions of package r-cran-randomforest |
Release | Version | Architectures |
bookworm | 4.7-1.1-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 4.7-1.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 4.7-1.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 4.6-12-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 4.6-10-1 | amd64,armel,armhf,i386 |
buster | 4.6-14-2 | amd64,arm64,armhf,i386 |
bullseye | 4.6-14-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
Debtags of package r-cran-randomforest: |
devel | lang:r, library |
field | biology, biology:bioinformatics, medicine |
interface | commandline |
role | devel-lib, shared-lib |
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License: DFSG free
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RandomForest implementuje algorytm lasów losowych Breimana (oparty na
oryginalnym kodzie Leo Breimana i Adele Cutler w języku Fortran) do
klasyfikacji i regresji. Może on być również stosowany w trybie
niekontrolowanym do oszacowywania odległości między punktami danych.
Technika ta korzysta z wielu drzew decyzyjnych i łączy ich indywidualne głosy.
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r-cran-rwave
GNU R time-frequency analysis of 1-D signals
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Versions of package r-cran-rwave |
Release | Version | Architectures |
sid | 2.6-5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.4-8-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 2.4-8-2 | amd64,arm64,armhf,i386 |
trixie | 2.6-5-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 2.6-5-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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A set of R functions which provide an environment for the Time-Frequency
analysis of 1-D signals (and especially for the wavelet and Gabor
transforms of noisy signals). It was originally written for Splus by
Rene Carmona, Bruno Torresani, and Wen L. Hwang, first at the University
of California at Irvine and then at Princeton University. Credit should
also be given to Andrea Wang whose functions on the dyadic wavelet
transform are included. Rwave is based on the book: "Practical
Time-Frequency Analysis: Gabor and Wavelet Transforms with an Implementation
in S", by Rene Carmona, Wen L. Hwang and Bruno Torresani (1998, eBook
ISBN:978008053942), Academic Press.
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r-cran-snowfall
GNU R easier cluster computing (based on snow)
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Versions of package r-cran-snowfall |
Release | Version | Architectures |
bookworm | 1.84-6.2-1 | all |
trixie | 1.84-6.3-1 | all |
sid | 1.84-6.3-1 | all |
buster | 1.84-6.1-2 | all |
bullseye | 1.84-6.1-3 | all |
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License: DFSG free
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Usability wrapper around snow for easier development of
parallel R programs. This package offers e.g. extended error
checks, and additional functions. All functions work in
sequential mode, too, if no cluster is present or wished.
Package is also designed as connector to the cluster management
tool sfCluster, but can also used without it.
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r-cran-waveslim
GNU R wavelet routines for 1-, 2- and 3-D signal processing
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Versions of package r-cran-waveslim |
Release | Version | Architectures |
bookworm | 1.8.4-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.8.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.8.4-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 1.8.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.7.5.1-1 | amd64,arm64,armhf,i386 |
upstream | 1.8.5 |
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License: DFSG free
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Basic wavelet routines for time series (1D), image (2D)
and array (3D) analysis. The code provided here is based on
wavelet methodology developed in Percival and Walden (2000);
Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet
transform (DTCWT) from Kingsbury (1999, 2001) as implemented by
Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All
figures in chapters 4-7 of GSW (2001) are reproducible using this
package and R code available at the book website(s) below.
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r-cran-wavethresh
GNU R wavelets statistics and transforms
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Versions of package r-cran-wavethresh |
Release | Version | Architectures |
bullseye | 4.6.8-3 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 4.6.8-2 | amd64,arm64,armhf,i386 |
bookworm | 4.7.2-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 4.7.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 4.7.2-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 4.7.3 |
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License: DFSG free
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Performs 1, 2 and 3D real and complex-valued wavelet transforms,
nondecimated transforms, wavelet packet transforms, nondecimated
wavelet packet transforms, multiple wavelet transforms,
complex-valued wavelet transforms, wavelet shrinkage for
various kinds of data, locally stationary wavelet time series,
nonstationary multiscale transfer function modeling, density
estimation.
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Official Debian packages with lower relevance
science-statistics
Pakiety naukowe Debiana związane ze statystykami
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Versions of package science-statistics |
Release | Version | Architectures |
trixie | 1.14.7 | all |
sid | 1.14.7 | all |
bookworm | 1.14.5 | all |
stretch | 1.7 | all |
buster | 1.10 | all |
bullseye | 1.14.2 | all |
jessie | 1.4 | all |
Debtags of package science-statistics: |
role | metapackage |
suite | debian |
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License: DFSG free
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Ten metapakiet jest częścią zestawu naukowego Debiana (Debian Pure Blend
"Debian Science") i instaluje pakiety związane z obliczeniami
statystycznymi. Zadania takie są powszechne i przydatne dla każdej
działalności naukowej. Pakiet zależy od wielu pakietów R, a także od innych
narzędzi przydatnych do tworzenia statystyk. Ponadto, sugerowane są zadania
z matematyki naukowej, co wymaga dodatkowej instalacji odpowiedniego
oprogramowania matematycznego.
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Packaging has started and developers might try the packaging code in VCS
rstudio
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Versions of package rstudio |
Release | Version | Architectures |
VCS | 2022.07.1+554-1 | all |
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License: AGPL-3.0
Debian package not available
Version: 2022.07.1+554-1
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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.
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