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r-zeitgebr 0.3.6
Propagated dependencies: r-waveletcomp@1.2 r-pracma@2.4.6 r-lomb@2.5.0 r-data-table@1.17.8 r-behavr@0.3.3
Channel: guix-cran
Location: guix-cran/packages/z.scm (guix-cran packages z)
Home page: https://github.com/rethomics/zeitgebr
Licenses: GPL 3
Build system: r
Synopsis: Analysis of Circadian Behaviours
Description:

Use behavioural variables to compute period, rhythmicity and other circadian parameters. Methods include computation of chi square periodograms (Sokolove and Bushell (1978) <DOI:10.1016/0022-5193(78)90022-X>), Lomb-Scargle periodograms (Lomb (1976) <DOI:10.1007/BF00648343>, Scargle (1982) <DOI:10.1086/160554>, Ruf (1999) <DOI:10.1076/brhm.30.2.178.1422>), and autocorrelation-based periodograms.

r-writexls 6.8.0
Dependencies: perl@5.36.0
Channel: guix
Location: gnu/packages/cran.scm (gnu packages cran)
Home page: https://github.com/marcschwartz/WriteXLS
Licenses: GPL 2+
Build system: r
Synopsis: Create Excel 2003 (XLS) and Excel 2007 (XLSX) files
Description:

This package provides a cross-platform Perl-based R function to create Excel 2003 (XLS) and Excel 2007 (XLSX) files from one or more data frames. Each data frame will be written to a separate named worksheet in the Excel spreadsheet. The worksheet name will be the name of the data frame it contains or can be specified by the user.

r-webfakes 1.4.0
Channel: guix
Location: gnu/packages/cran.scm (gnu packages cran)
Home page: https://webfakes.r-lib.org/
Licenses: Expat
Build system: r
Synopsis: Fake web apps for HTTP testing
Description:

This package lets you create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. It can parse various HTTP request bodies. It can send JSON data or files from the disk. It includes a web app that implements the httpbin.org web service.

r-gse13015 1.18.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-preprocesscore@1.72.0 r-geoquery@2.78.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GSE13015
Licenses: FSDG-compatible
Build system: r
Synopsis: GEO accession data GSE13015_GPL6106 as a SummarizedExperiment
Description:

Microarray expression matrix platform GPL6106 and clinical data for 67 septicemic patients and made them available as GEO accession [GSE13015](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13015). GSE13015 data have been parsed into a SummarizedExperiment object available in ExperimentHub. This data data could be used as an example supporting BloodGen3Module R package.

r-bedassle 1.6.1
Propagated dependencies: r-matrixcalc@1.0-6 r-mass@7.3-65 r-emdbook@1.3.14
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BEDASSLE
Licenses: GPL 2+
Build system: r
Synopsis: Quantifies Effects of Geo/Eco Distance on Genetic Differentiation
Description:

This package provides functions that allow users to quantify the relative contributions of geographic and ecological distances to empirical patterns of genetic differentiation on a landscape. Specifically, we use a custom Markov chain Monte Carlo (MCMC) algorithm, which is used to estimate the parameters of the inference model, as well as functions for performing MCMC diagnosis and assessing model adequacy.

r-bmixture 1.7
Propagated dependencies: r-bdgraph@2.74
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://www.uva.nl/profile/a.mohammadi
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Estimation for Finite Mixture of Distributions
Description:

This package provides statistical tools for Bayesian estimation of mixture distributions, mainly a mixture of Gamma, Normal, and t-distributions. The package is implemented based on the Bayesian literature for the finite mixture of distributions, including Mohammadi and et al. (2013) <doi:10.1007/s00180-012-0323-3> and Mohammadi and Salehi-Rad (2012) <doi:10.1080/03610918.2011.588358>.

r-bnstruct 1.0.15
Propagated dependencies: r-igraph@2.2.1 r-bitops@1.0-9
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bnstruct
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Bayesian Network Structure Learning from Data with Missing Values
Description:

Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference.

r-corrfuns 1.2
Propagated dependencies: r-rfast2@0.1.5.5 r-rfast@2.1.5.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=corrfuns
Licenses: GPL 2+
Build system: r
Synopsis: Correlation Coefficient Related Functions
Description:

Many correlation coefficient related functions are offered, such as correlations, partial correlations and hypothesis testing using asymptotic tests and computer intensive methods (bootstrap and permutation). References include Mardia K.V., Kent J.T. and Bibby J.M. (1979). "Multivariate Analysis". ISBN: 978-0124712522. London: Academic Press and Owen A. B. (2001). "Empirical likelihood". Chapman and Hall/CRC Press. ISBN: 9781584880714.

r-chromseq 0.1.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/MSQ-123/chromseq
Licenses: Artistic License 2.0
Build system: r
Synopsis: Split Chromosome 'Fasta' File
Description:

Chromosome files in the Fasta format usually contain large sequences like human genome. Sometimes users have to split these chromosomes into different files according to their chromosome number. The chromseq can help to handle this. So the selected chromosome sequence can be used for downstream analysis like motif finding. Howard Y. Chang(2019) <doi:10.1038/s41587-019-0206-z>.

r-healthyr 0.2.2
Propagated dependencies: r-writexl@1.5.4 r-timetk@2.9.1 r-tibble@3.3.0 r-stringr@1.6.0 r-sqldf@0.4-11 r-scales@1.4.0 r-rlang@1.1.6 r-purrr@1.2.0 r-plotly@4.11.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/spsanderson/healthyR
Licenses: Expat
Build system: r
Synopsis: Hospital Data Analysis Workflow Tools
Description:

Hospital data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include average length of stay, readmission rates, average net pay amounts by service lines just to name a few. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.

r-jmastats 0.3.0
Propagated dependencies: r-xml2@1.5.0 r-units@1.0-0 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-sf@1.0-23 r-rvest@1.0.5 r-rlang@1.1.6 r-readr@2.1.6 r-rappdirs@0.3.3 r-purrr@1.2.0 r-lubridate@1.9.4 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-crayon@1.5.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://uribo.github.io/jmastats/
Licenses: Expat
Build system: r
Synopsis: Download Weather Data from Japan Meteorological Agency Website
Description:

This package provides features that allow users to download weather data published by the Japan Meteorological Agency (JMA) website (<https://www.jma.go.jp/jma/index.html>). The data includes information dating back to 1976 and aligns with the categories available on the website. Additionally, users can process the best track data of typhoons and easily handle earthquake record files.

r-mosclust 1.0.2
Propagated dependencies: r-clusterv@1.1.1 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://valentini.di.unimi.it/SW/mosclust/
Licenses: GPL 2+
Build system: r
Synopsis: Model Order Selection for Clustering
Description:

Stability based methods for model order selection in clustering problems (Valentini, G (2007), <doi:10.1093/bioinformatics/btl600>). Using multiple perturbations of the data the stability of clustering solutions is assessed. Different perturbations may be used: resampling techniques, random projections and noise injection. Stability measures for the estimate of clustering solutions and statistical tests to assess their significance are provided.

r-nbdesign 2.0.0
Propagated dependencies: r-pweall@1.3.0.1 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NBDesign
Licenses: GPL 2+
Build system: r
Synopsis: Design and Monitoring of Clinical Trials with Negative Binomial Endpoint
Description:

Calculate various functions needed for design and monitoring clinical trials with negative binomial endpoint with variable follow-up. This version has a few changes compared to the previous version 1.0.0, including (1) correct a typo in Type 1 censoring, mtbnull=bnull and (2) restructure the code to account for shape parameter equal to zero, i.e. Poisson scenario.

r-optmatch 0.10.8
Propagated dependencies: r-tibble@3.3.0 r-rlemon@0.2.1 r-rcpp@1.1.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: http://optmat.ch
Licenses: Expat
Build system: r
Synopsis: Functions for Optimal Matching
Description:

Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies ('Hansen and Klopfer 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.

r-phidelta 1.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=phiDelta
Licenses: GPL 2+
Build system: r
Synopsis: Tool for Phi Delta Analysis of Features
Description:

Analysis of features by phi delta diagrams. In particular, functions for reading data and calculating phi and delta as well as the functionality to plot it. Moreover it is possible to do further analysis on the data by generating rankings. For more information on phi delta diagrams, see also Giuliano Armano (2015) <doi:10.1016/j.ins.2015.07.028>.

r-pvebayes 0.2.1
Propagated dependencies: r-wacolors@0.3.1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-magrittr@2.0.4 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggfittext@0.10.2 r-ggdist@3.3.3 r-data-table@1.17.8 r-cvxr@1.0-15
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/YihaoTancn/pvEBayes
Licenses: GPL 3
Build system: r
Synopsis: Empirical Bayes Methods for Pharmacovigilance
Description:

This package provides a suite of empirical Bayes methods to use in pharmacovigilance. Contains various model fitting and post-processing functions. For more details see Tan et al. (2025) <doi:10.48550/arXiv.2502.09816>, <doi:10.48550/arXiv.2512.01057>; Koenker and Mizera (2014) <doi:10.1080/01621459.2013.869224>; Efron (2016) <doi:10.1093/biomet/asv068>.

r-srttools 1.2.0
Propagated dependencies: r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ChiHangChen/SRTtools
Licenses: GPL 2+
Build system: r
Synopsis: Adjust Srt File to Get Better Experience when Watching Movie
Description:

Srt file is a common subtitle format for videos, it contains subtitle and when the subtitle showed. This package is for align time of srt file, and also change color, style and position of subtitle in videos, the srt file will be read as a vector into R, and can be write into srt file after modified using this package.

r-shinysbm 0.2.0
Propagated dependencies: r-visnetwork@2.1.4 r-stringr@1.6.0 r-shinydashboard@0.7.3 r-shinyalert@3.1.0 r-shiny@1.11.1 r-sbm@0.4.7 r-rmarkdown@2.30 r-purrr@1.2.0 r-patchwork@1.3.2 r-magrittr@2.0.4 r-golem@0.5.1 r-ggplot2@4.0.1 r-fresh@0.2.2 r-flextable@0.9.10 r-dt@0.34.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-config@0.3.2 r-colourpicker@1.3.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://shinysbm-theodore-vanrenterghem-b12616c23cfbfb3f0fe520178bcb95a.pages-forge.inrae.fr/
Licenses: Expat
Build system: r
Synopsis: 'shiny' Application to Use the Stochastic Block Model
Description:

This package provides a shiny interface for a simpler use of the sbm R package. It also contains useful functions to easily explore the sbm package results. With this package you should be able to use the stochastic block model without any knowledge in R, get automatic reports and nice visuals, as well as learning the basic functions of sbm'.

r-simstudy 0.9.2
Propagated dependencies: r-rcpp@1.1.0 r-pbv@0.5-47 r-mvnfast@0.2.8 r-glue@1.8.0 r-fastglm@0.0.3 r-data-table@1.17.8 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/kgoldfeld/simstudy
Licenses: GPL 3
Build system: r
Synopsis: Simulation of Study Data
Description:

Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).

r-rfempimp 2.1.8
Propagated dependencies: r-ranger@0.17.0 r-mice@3.18.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/shangzhi-hong/RfEmpImp
Licenses: GPL 3
Build system: r
Synopsis: Multiple Imputation using Chained Random Forests
Description:

An R package for multiple imputation using chained random forests. Implemented methods can handle missing data in mixed types of variables by using prediction-based or node-based conditional distributions constructed using random forests. For prediction-based imputation, the method based on the empirical distribution of out-of-bag prediction errors of random forests and the method based on normality assumption for prediction errors of random forests are provided for imputing continuous variables. And the method based on predicted probabilities is provided for imputing categorical variables. For node-based imputation, the method based on the conditional distribution formed by the predicting nodes of random forests, and the method based on proximity measures of random forests are provided. More details of the statistical methods can be found in Hong et al. (2020) <arXiv:2004.14823>.

r-revtools 0.4.1
Propagated dependencies: r-viridislite@0.4.2 r-topicmodels@0.2-17 r-tm@0.7-16 r-stringdist@0.9.15 r-snowballc@0.7.1 r-slam@0.1-55 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-plotly@4.11.0 r-ngram@3.2.3 r-modeltools@0.2-24 r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://revtools.net
Licenses: GPL 3
Build system: r
Synopsis: Tools to Support Evidence Synthesis
Description:

Researchers commonly need to summarize scientific information, a process known as evidence synthesis'. The first stage of a synthesis process (such as a systematic review or meta-analysis) is to download a list of references from academic search engines such as Web of Knowledge or Scopus'. The traditional approach to systematic review is then to sort these data manually, first by locating and removing duplicated entries, and then screening to remove irrelevant content by viewing titles and abstracts (in that order). revtools provides interfaces for each of these tasks. An alternative approach, however, is to draw on tools from machine learning to visualise patterns in the corpus. In this case, you can use revtools to render ordinations of text drawn from article titles, keywords and abstracts, and interactively select or exclude individual references, words or topics.

radio-tool 0.3.0
Dependencies: libusb@1.0.25
Channel: guix
Location: gnu/packages/radio.scm (gnu packages radio)
Home page: https://github.com/v0l/radio_tool
Licenses: GPL 3+
Build system: cmake
Synopsis: Radio Firmware tool
Description:

radio_tool is a utility for reading, writing, and manipulating firmware/codeplugs on the following radios: TYT MD-2017, TYT MD-9600, TYT MD-UV380, TYT MD-UV390, TYT MD-390, TYT MD-380, TYT MD-446, TYT MD-280, Baofeng DM-1701, Baofeng DM1801, Baofeng RD-5R, Connect Systems CS800D, Ailunce HD1, Yaesu FT-70DR, and the Radioddity GD-77.

r-absorber 1.0
Propagated dependencies: r-sparsegl@1.1.1 r-matrix@1.7-4 r-mass@7.3-65 r-irlba@2.3.5.1 r-ggplot2@4.0.1 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=absorber
Licenses: GPL 2
Build system: r
Synopsis: Variable Selection in Nonparametric Models using B-Splines
Description:

This package provides a variable selection method using B-Splines in multivariate nOnparametric Regression models Based on partial dErivatives Regularization (ABSORBER) implements a novel variable selection method in a nonlinear multivariate model using B-splines. For further details we refer the reader to the paper Savino, M. E. and Lévy-Leduc, C. (2024), <https://hal.science/hal-04434820>.

r-aribrain 0.2
Propagated dependencies: r-rnifti@1.8.0 r-plyr@1.8.9 r-hommel@1.8
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=ARIbrain
Licenses: GPL 2+
Build system: r
Synopsis: All-Resolution Inference
Description:

It performs All-Resolutions Inference (ARI) on functional Magnetic Resonance Image (fMRI) data. As a main feature, it estimates lower bounds for the proportion of active voxels in a set of clusters as, for example, given by a cluster-wise analysis. The method is described in Rosenblatt, Finos, Weeda, Solari, Goeman (2018) <doi:10.1016/j.neuroimage.2018.07.060>.

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