_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-semicontmanova 0.2
Propagated dependencies: r-mvtnorm@1.3-3 r-matrixcalc@1.0-6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=semicontMANOVA
Licenses: GPL 2
Build system: r
Synopsis: Multivariate ANalysis of VAriance with Ridge Regularization for Semicontinuous High-Dimensional Data
Description:

This package implements Multivariate ANalysis Of VAriance (MANOVA) parameters inference and test with regularization for semicontinuous high-dimensional data. The method can be applied also in presence of low-dimensional data. The p-value can be obtained through asymptotic distribution or using a permutation procedure. The package gives also the possibility to simulate this type of data. Method is described in Elena Sabbioni, Claudio Agostinelli and Alessio Farcomeni (2025) A regularized MANOVA test for semicontinuous high-dimensional data. Biometrical Journal, 67:e70054. DOI <doi:10.1002/bimj.70054>, arXiv DOI <doi:10.48550/arXiv.2401.04036>.

r-stepmetrics 1.0.3
Propagated dependencies: r-physicalactivity@0.2-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jhmigueles/stepmetrics
Licenses: AGPL 3+
Build system: r
Synopsis: Calculate Step and Cadence Metrics from Wearable Data
Description:

This package provides functions to calculate step- and cadence-based metrics from timestamped accelerometer and wearable device data. Supports CSV and AGD files from ActiGraph devices, CSV files from Fitbit devices, and step counts derived with R package GGIR <https://github.com/wadpac/GGIR>, with automatic handling of epoch lengths from 1 to 60 seconds. Metrics include total steps, cadence peaks, minutes and steps in predefined cadence bands, and time and steps in moderate-to-vigorous physical activity (MVPA). Methods and thresholds are informed by the literature, e.g., Tudor-Locke and Rowe (2012) <doi:10.2165/11599170-000000000-00000>, Barreira et al. (2012) <doi:10.1249/MSS.0b013e318254f2a3>, and Tudor-Locke et al. (2018) <doi:10.1136/bjsports-2017-097628>. The package record is also available on Zenodo (2023) <doi:10.5281/zenodo.7858094>.

r-sudokualt 0.2-1
Propagated dependencies: r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sudokuAlt
Licenses: GPL 2+
Build system: r
Synopsis: Tools for Making and Spoiling Sudoku Games
Description:

This package provides tools for making, retrieving, displaying and solving sudoku games. This package is an alternative to the earlier sudoku-solver package, sudoku'. The present package uses a slightly different algorithm, has a simpler coding and presents a few more sugar tools, such as plot and print methods. Solved sudoku games are of some interest in Experimental Design as examples of Latin Square designs with additional balance constraints.

r-shinychakraui 1.1.1
Propagated dependencies: r-stringr@1.6.0 r-shiny@1.11.1 r-rlang@1.1.6 r-reactr@0.6.1 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-formatr@1.14 r-fontawesome@0.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/stla/shinyChakraUI
Licenses: GPL 3+
Build system: r
Synopsis: Wrapper of the 'React' Library 'Chakra UI' for 'Shiny'
Description:

Makes the React library Chakra UI usable in Shiny apps. Chakra UI components include alert dialogs, drawers (sliding panels), menus, modals, popovers, sliders, and more.

r-sdclog 0.5.1
Propagated dependencies: r-mathjaxr@1.8-0 r-data-table@1.17.8 r-cli@3.6.5 r-checkmate@2.3.3 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/matthiasgomolka/sdcLog
Licenses: GPL 3
Build system: r
Synopsis: Tools for Statistical Disclosure Control in Research Data Centers
Description:

This package provides tools for researchers to explicitly show that their results comply to rules for statistical disclosure control imposed by research data centers. These tools help in checking descriptive statistics and models and in calculating extreme values that are not individual data. Also included is a simple function to create log files. The methods used here are described in the "Guidelines for the checking of output based on microdata research" by Bond, Brandt, and de Wolf (2015) <https://cros.ec.europa.eu/system/files/2024-02/Output-checking-guidelines.pdf>.

r-simidm 0.1.0
Propagated dependencies: r-survival@3.8-3 r-parallelly@1.45.1 r-mstate@0.3.3 r-future@1.68.0 r-furrr@0.3.1 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/insightsengineering/simIDM/
Licenses: ASL 2.0
Build system: r
Synopsis: Simulating Oncology Trials using an Illness-Death Model
Description:

Based on the illness-death model a large number of clinical trials with oncology endpoints progression-free survival (PFS) and overall survival (OS) can be simulated, see Meller, Beyersmann and Rufibach (2019) <doi:10.1002/sim.8295>. The simulation set-up allows for random and event-driven censoring, an arbitrary number of treatment arms, staggered study entry and drop-out. Exponentially, Weibull and piecewise exponentially distributed survival times can be generated. The correlation between PFS and OS can be calculated.

r-slidingwindows 0.2.0
Propagated dependencies: r-tsentropies@0.9 r-performanceanalytics@2.0.8 r-nonlineartseries@0.3.1 r-dcca@0.1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/efguedes/SlidingWindows
Licenses: GPL 3
Build system: r
Synopsis: Methods for Time Series Analysis
Description:

This package provides a collection of functions to perform Detrended Fluctuation Analysis (DFA exponent), GUEDES et al. (2019) <doi:10.1016/j.physa.2019.04.132> , Detrended cross-correlation coefficient (RHODCCA), GUEDES & ZEBENDE (2019) <doi:10.1016/j.physa.2019.121286>, DMCA cross-correlation coefficient and Detrended multiple cross-correlation coefficient (DMC), GUEDES & SILVA-FILHO & ZEBENDE (2018) <doi:10.1016/j.physa.2021.125990>, both with sliding windows approach.

r-seset 1.0.1
Propagated dependencies: r-rdpack@2.6.4 r-matrix@1.7-4 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SEset
Licenses: GPL 3
Build system: r
Synopsis: Computing Statistically-Equivalent Path Models
Description:

This package provides tools to compute and analyze the set of statistically-equivalent (Gaussian, linear) path models which generate the input precision or (partial) correlation matrix. This procedure is useful for understanding how statistical network models such as the Gaussian Graphical Model (GGM) perform as causal discovery tools. The statistical-equivalence set of a given GGM expresses the uncertainty we have about the sign, size and direction of directed relationships based on the weights matrix of the GGM alone. The derivation of the equivalence set and its use for understanding GGMs as causal discovery tools is described by Ryan, O., Bringmann, L.F., & Schuurman, N.K. (2022) <doi: 10.31234/osf.io/ryg69>.

r-sae-projection 0.1.5
Propagated dependencies: r-yardstick@1.3.2 r-workflows@1.3.0 r-tune@2.0.1 r-tidymodels@1.4.1 r-themis@1.0.3 r-survey@4.4-8 r-rsample@1.3.1 r-rlang@1.1.6 r-recipes@1.3.1 r-ranger@0.17.0 r-randomforest@4.7-1.2 r-parsnip@1.3.3 r-lightgbm@4.6.0 r-dplyr@1.1.4 r-doparallel@1.0.17 r-cli@3.6.5 r-caret@7.0-1 r-bonsai@0.4.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Alfrzlp/sae.projection
Licenses: Expat
Build system: r
Synopsis: Small Area Estimation Using Model-Assisted Projection Method
Description:

Combines information from two independent surveys using a model-assisted projection method. Designed for survey sampling scenarios where a large sample collects only auxiliary information (Survey 1) and a smaller sample provides data on both variables of interest and auxiliary variables (Survey 2). Implements a working model to generate synthetic values of the variable of interest by fitting the model to Survey 2 data and predicting values for Survey 1 based on its auxiliary variables (Kim & Rao, 2012) <doi:10.1093/biomet/asr063>.

r-sim-plfn 1.0
Propagated dependencies: r-fuzzynumbers@0.4-7 r-distrib@1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=Sim.PLFN
Licenses: LGPL 3+
Build system: r
Synopsis: Simulation of Piecewise Linear Fuzzy Numbers
Description:

The definition of fuzzy random variable and the methods of simulation from fuzzy random variables are two challenging statistical problems in three recent decades. This package is organized based on a special definition of fuzzy random variable and simulate fuzzy random variable by Piecewise Linear Fuzzy Numbers (PLFNs); see Coroianua et al. (2013) <doi:10.1016/j.fss.2013.02.005> for details about PLFNs. Some important statistical functions are considered for obtaining the membership function of main statistics, such as mean, variance, summation, standard deviation and coefficient of variance. Some of applied advantages of Sim.PLFN package are: (1) Easily generating / simulation a random sample of PLFN, (2) drawing the membership functions of the simulated PLFNs or the membership function of the statistical result, and (3) Considering the simulated PLFNs for arithmetic operation or importing into some statistical computation. Finally, it must be mentioned that Sim.PLFN package works on the basis of FuzzyNumbers package.

r-scenfire 0.1.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-terra@1.8-86 r-stringr@1.6.0 r-sf@1.0-23 r-rlang@1.1.6 r-readr@2.1.6 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scenfire
Licenses: Expat
Build system: r
Synopsis: Post-Processing Algorithm for Integrating Wildfire Simulations
Description:

This package provides a specialized selection algorithm designed to align simulated fire perimeters with specific fire size distribution scenarios. The foundation of this approach lies in generating a vast collection of plausible simulated fires across a wide range of conditions, assuming a random pattern of ignition. The algorithm then assembles individual fire perimeters based on their specific probabilities of occurrence, e.g., determined by (i) the likelihood of ignition and (ii) the probability of particular fire-weather scenarios, including wind speed and direction. Implements the method presented in Rodrigues (2025a) <doi:10.5194/egusphere-egu25-8974>. Demo data and code examples can be found in Rodrigues (2025b) <doi:10.5281/zenodo.15282605>.

r-syllabifyr 0.1.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-purrr@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=syllabifyr
Licenses: Expat
Build system: r
Synopsis: Syllabifier for CMU Dictionary Transcriptions
Description:

This package implements tidy syllabification of transcription. Based on @kylebgorman's python implementation <https://github.com/kylebgorman/syllabify>.

r-shinyexprportal 1.2.1
Propagated dependencies: r-yaml@2.3.10 r-vegawidget@0.5.0 r-tidyr@1.3.1 r-shinyhelper@0.3.2 r-shiny@1.11.1 r-rlang@1.1.6 r-rfast@2.1.5.2 r-qvalue@2.42.0 r-markdown@2.0 r-iheatmapr@0.7.1 r-htmltools@0.5.8.1 r-dt@0.34.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-config@0.3.2 r-cli@3.6.5 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://c4tb.github.io/shinyExprPortal/
Licenses: Expat
Build system: r
Synopsis: Configurable 'shiny' Portal for Sharing Analysis of Molecular Expression Data
Description:

Enables deploying configuration file-based shiny apps with minimal programming for interactive exploration and analysis showcase of molecular expression data. For exploration, supports visualization of correlations between rows of an expression matrix and a table of observations, such as clinical measures, and comparison of changes in expression over time. For showcase, enables visualizing the results of differential expression from package such as limma', co-expression modules from WGCNA and lower dimensional projections.

r-survex 1.2.0
Propagated dependencies: r-survival@3.8-3 r-pec@2025.06.24 r-patchwork@1.3.2 r-kernelshap@0.9.1 r-ggplot2@4.0.1 r-dalex@2.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://modeloriented.github.io/survex/
Licenses: GPL 3+
Build system: r
Synopsis: Explainable Machine Learning in Survival Analysis
Description:

Survival analysis models are commonly used in medicine and other areas. Many of them are too complex to be interpreted by human. Exploration and explanation is needed, but standard methods do not give a broad enough picture. survex provides easy-to-apply methods for explaining survival models, both complex black-boxes and simpler statistical models. They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023) <doi:10.1016/j.knosys.2022.110234>, SurvLIME described in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.

r-sfislands 1.1.2
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-spdep@1.4-1 r-sf@1.0-23 r-purrr@1.2.0 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-broom-mixed@0.2.9.7
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/horankev/sfislands
Licenses: Expat
Build system: r
Synopsis: Streamlines the Process of Fitting Areal Spatial Models
Description:

Helpers for addressing the issue of disconnected spatial units. It allows for convenient adding and removal of neighbourhood connectivity between areal units prior to modelling, with the visual aid of maps. Post-modelling, it reduces the human workload for extracting, tidying and mapping predictions from areal models.

r-scoredec 0.1.2
Propagated dependencies: r-rfast@2.1.5.2 r-rcpp@1.1.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/cadam00/scoredec
Licenses: GPL 3
Build system: r
Synopsis: S-Core Graph Decomposition
Description:

S-Core Graph Decomposition algorithm for graphs. This is a method for decomposition of a weighted graph, as proposed by Eidsaa and Almaas (2013) <doi:10.1103/PhysRevE.88.062819>. The high speed and the low memory usage make it suitable for large graphs.

r-shinylight 1.2
Propagated dependencies: r-later@1.4.4 r-jsonlite@2.0.0 r-httpuv@1.6.16
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shinylight
Licenses: GPL 3
Build system: r
Synopsis: Web Interface to 'R' Functions
Description:

Web front end for your R functions producing plots or tables. If you have a function or set of related functions, you can make them available over the internet through a web browser. This is the same motivation as the shiny package, but note that the development of shinylight is not in any way linked to that of shiny (beyond the use of the httpuv package). You might prefer shinylight to shiny if you want a lighter weight deployment with easier horizontal scaling, or if you want to develop your front end yourself in JavaScript and HTML just using a lightweight remote procedure call interface to your R code on the server.

r-senstrat 1.0.3
Propagated dependencies: r-mass@7.3-65 r-biasedurn@2.0.12
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=senstrat
Licenses: GPL 2
Build system: r
Synopsis: Sensitivity Analysis for Stratified Observational Studies
Description:

Sensitivity analysis in unmatched observational studies, with or without strata. The main functions are sen2sample() and senstrat(). See Rosenbaum, P. R. and Krieger, A. M. (1990), JASA, 85, 493-498, <doi:10.1080/01621459.1990.10476226> and Gastwirth, Krieger and Rosenbaum (2000), JRSS-B, 62, 545รข 555 <doi:10.1111/1467-9868.00249> .

r-sk4fga 0.1.1
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/tobyhayward13/SCI118UOA_ForensicGlassAnalysis
Licenses: GPL 2+
Build system: r
Synopsis: Scott-Knott for Forensic Glass Analysis
Description:

In forensics, it is common and effective practice to analyse glass fragments from the scene and suspects to gain evidence of placing a suspect at the crime scene. This kind of analysis involves comparing the physical and chemical attributes of glass fragments that exist on both the person and at the crime scene, and assessing the significance in a likeness that they share. The package implements the Scott-Knott Modification 2 algorithm (SKM2) (Christopher M. Triggs and James M. Curran and John S. Buckleton and Kevan A.J. Walsh (1997) <doi:10.1016/S0379-0738(96)02037-3> "The grouping problem in forensic glass analysis: a divisive approach", Forensic Science International, 85(1), 1--14) for small sample glass fragment analysis using the refractive index (ri) of a set of glass samples. It also includes an experimental multivariate analog to the Scott-Knott algorithm for similar analysis on glass samples with multiple chemical concentration variables and multiple samples of the same item; testing against the Hotellings T^2 distribution (J.M. Curran and C.M. Triggs and J.R. Almirall and J.S. Buckleton and K.A.J. Walsh (1997) <doi:10.1016/S1355-0306(97)72197-X> "The interpretation of elemental composition measurements from forensic glass evidence", Science & Justice, 37(4), 241--244).

r-stors 1.0.1
Propagated dependencies: r-rlang@1.1.6 r-microbenchmark@1.5.0 r-digest@0.6.39 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://ahmad-alqabandi.github.io/stors/
Licenses: Expat
Build system: r
Synopsis: Step Optimised Rejection Sampling
Description:

Fast and efficient sampling from general univariate probability density functions. Implements a rejection sampling approach designed to take advantage of modern CPU caches and minimise evaluation of the target density for most samples. Many standard densities are internally implemented in C for high performance, with general user defined densities also supported. A paper describing the methodology will be released soon.

r-seedmaker 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-dplyr@1.1.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/hdhshowalter/SeedMaker
Licenses: Expat
Build system: r
Synopsis: Generate a Collection of Seeds from a Single Seed
Description:

This package provides a mechanism for easily generating and organizing a collection of seeds from a single seed, which may be subsequently used to ensure reproducibility in processes/pipelines that utilize multiple random components (e.g., trial simulation).

r-soccer 0.1.1
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ekstroem/socceR
Licenses: GPL 2+
Build system: r
Synopsis: Evaluating Sport Tournament Predictions
Description:

This package provides functions for evaluating tournament predictions, simulating results from individual soccer matches and tournaments. See <http://sandsynligvis.dk/2018/08/03/world-cup-prediction-winners/> for more information.

r-stacomirtools 0.6.0.1
Propagated dependencies: r-xtable@1.8-4 r-rpostgres@1.4.8 r-rodbc@1.3-26.1 r-pool@1.0.4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stacomirtools
Licenses: GPL 2+
Build system: r
Synopsis: Connection Class for Package stacomiR
Description:

S4 class wrappers for the ODBC and Pool DBI connection, also provides some utilities to paste small datasets to clipboard, rename columns. It is used by the package stacomiR for connections to the database. Development versions of stacomiR are available in R-forge.

r-spacenet 1.2
Propagated dependencies: r-vegan@2.7-2 r-sna@2.8 r-rfast@2.1.5.2 r-rcpptn@0.2-2 r-permute@0.9-8 r-mclust@6.1.2 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spaceNet
Licenses: GPL 2+
Build system: r
Synopsis: Latent Space Models for Multidimensional Networks
Description:

Latent space models for multivariate networks (multiplex) estimated via MCMC algorithm. See D Angelo et al. (2018) <arXiv:1803.07166> and D Angelo et al. (2018) <arXiv:1807.03874>.

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