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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-simvitd 1.0.3
Propagated dependencies: r-simpleboot@1.1-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SimVitD
Licenses: GPL 2+
Build system: r
Synopsis: Simulation Tools for Planning Vitamin D Studies
Description:

Simulation tools for planning Vitamin D studies. Individual vitamin D status profiles are simulated, modelling population heterogeneity in trial arms. Exposures to infectious agents are generated, with infection depending on vitamin D status.

r-sdcnway 1.0.1
Propagated dependencies: r-rdpack@2.6.4 r-plyr@1.8.9 r-mass@7.3-65 r-ggplot2@4.0.1 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=SDCNway
Licenses: GPL 2
Build system: r
Synopsis: Tools to Evaluate Disclosure Risk
Description:

This package provides tools for calculating disclosure risk measures for microdata, including record-level and file-level measures. The record-level disclosure risk is estimated primarily using exhaustive tabulation. The file-level disclosure risk is estimated by fitting loglinear models on the observed sample counts in cells formed by key variables and their interactions. Funded by the National Center for Education Statistics. See Skinner and Shlomo (2008) <doi:10.1198/016214507000001328> for a description of the file-level risk measures and the loglinear model approach.

r-sanvi 0.1.1
Propagated dependencies: r-scales@1.4.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-matrixstats@1.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/fradenti/SANvi
Licenses: Expat
Build system: r
Synopsis: Fitting Shared Atoms Nested Models via Variational Bayes
Description:

An efficient tool for fitting the nested common and shared atoms models using variational Bayes approximate inference for fast computation. Specifically, the package implements the common atoms model (Denti et al., 2023), its finite version (D'Angelo et al., 2023), and a hybrid finite-infinite model. All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyze the results of the fitting procedure. References: Denti, Camerlenghi, Guindani, Mira (2023) <doi:10.1080/01621459.2021.1933499>, Dâ Angelo, Canale, Yu, Guindani (2023) <doi:10.1111/biom.13626>.

r-simdd 1.1-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=simdd
Licenses: GPL 2
Build system: r
Synopsis: Simulation of Fisher Bingham and Related Directional Distributions
Description:

Simulation methods for the Fisher Bingham distribution on the unit sphere, the matrix Bingham distribution on a Grassmann manifold, the matrix Fisher distribution on SO(3), and the bivariate von Mises sine model on the torus. The methods use an acceptance/rejection simulation algorithm for the Bingham distribution and are described fully by Kent, Ganeiber and Mardia (2018) <doi:10.1080/10618600.2017.1390468>. These methods supersede earlier MCMC simulation methods and are more general than earlier simulation methods. The methods can be slower in specific situations where there are existing non-MCMC simulation methods (see Section 8 of Kent, Ganeiber and Mardia (2018) <doi:10.1080/10618600.2017.1390468> for further details).

r-skater 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-kinship2@1.9.6.2 r-dplyr@1.1.4 r-corrr@0.4.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/signaturescience/skater
Licenses: Expat
Build system: r
Synopsis: Utilities for SNP-Based Kinship Analysis
Description:

Utilities for single nucleotide polymorphism (SNP) based kinship analysis testing and evaluation. The skater package contains functions for importing, parsing, and analyzing pedigree data, performing relationship degree inference, benchmarking relationship degree classification, and summarizing identity by descent (IBD) segment data. Package functions and methods are described in Turner et al. (2021) "skater: An R package for SNP-based Kinship Analysis, Testing, and Evaluation" <doi:10.1101/2021.07.21.453083>.

r-stylo 0.7.5
Propagated dependencies: r-tsne@0.1-3.1 r-tcltk2@1.6.1 r-pamr@1.57 r-lattice@0.22-7 r-e1071@1.7-16 r-class@7.3-23 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/computationalstylistics/stylo
Licenses: GPL 3+
Build system: r
Synopsis: Stylometric Multivariate Analyses
Description:

Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.

r-sleacr 0.1.3
Propagated dependencies: r-parallelly@1.45.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://nutriverse.io/sleacr/
Licenses: GPL 3+
Build system: r
Synopsis: Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) Tools
Description:

In the recent past, measurement of coverage has been mainly through two-stage cluster sampled surveys either as part of a nutrition assessment or through a specific coverage survey known as Centric Systematic Area Sampling (CSAS). However, such methods are resource intensive and often only used for final programme evaluation meaning results arrive too late for programme adaptation. SLEAC, which stands for Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage, is a low resource method designed specifically to address this limitation and is used regularly for monitoring, planning and importantly, timely improvement to programme quality, both for agency and Ministry of Health (MoH) led programmes. SLEAC is designed to complement the Semi-quantitative Evaluation of Access and Coverage (SQUEAC) method. This package provides functions for use in conducting a SLEAC assessment.

r-sbde 1.0-2
Propagated dependencies: r-extremefit@1.1.0 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sbde
Licenses: GPL 2
Build system: r
Synopsis: Semiparametric Bayesian Density Estimation
Description:

Offers Bayesian semiparametric density estimation and tail-index estimation for heavy tailed data, by using a parametric, tail-respecting transformation of the data to the unit interval and then modeling the transformed data with a purely nonparametric logistic Gaussian process density prior. Based on Tokdar et al. (2022) <doi:10.1080/01621459.2022.2104727>.

r-sensiat 0.3.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-rlang@1.1.6 r-rcpp@1.1.0 r-purrr@1.2.0 r-pracma@2.4.6 r-orthogonalsplinebasis@0.1.7 r-mave@1.3.12 r-mass@7.3-65 r-kernsmooth@2.23-26 r-glue@1.8.0 r-ggplot2@4.0.1 r-generics@0.1.4 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/UofUEpiBio/SensIAT
Licenses: Expat
Build system: r
Synopsis: Sensitivity Analysis for Irregular Assessment Times
Description:

Sensitivity analysis for trials with irregular and informative assessment times, based on a new influence function-based, augmented inverse intensity-weighted estimator.

r-spacesxyz 1.6-0
Propagated dependencies: r-logger@0.4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spacesXYZ
Licenses: GPL 3+
Build system: r
Synopsis: CIE XYZ and some of Its Derived Color Spaces
Description:

This package provides functions for converting among CIE XYZ, xyY, Lab, and Luv. Calculate Correlated Color Temperature (CCT) and the Planckian and daylight loci. The XYZs of some standard illuminants and some standard linear chromatic adaptation transforms (CATs) are included. Three standard color difference metrics are included, plus the forward direction of the CIECAM02 color appearance model.

r-spatialdownscaling 0.1.2
Dependencies: python@3.11.14
Propagated dependencies: r-tensorflow@2.20.0 r-rdpack@2.6.4 r-raster@3.6-32 r-magrittr@2.0.4 r-keras3@1.5.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SpatialDownscaling
Licenses: GPL 3
Build system: r
Synopsis: Methods for Spatial Downscaling Using Deep Learning
Description:

The aim of the spatial downscaling is to increase the spatial resolution of the gridded geospatial input data. This package contains two deep learning based spatial downscaling methods, super-resolution deep residual network (SRDRN) (Wang et al., 2021 <doi:10.1029/2020WR029308>) and UNet (Ronneberger et al., 2015 <doi:10.1007/978-3-319-24574-4_28>), along with a statistical baseline method bias correction and spatial disaggregation (Wood et al., 2004 <doi:10.1023/B:CLIM.0000013685.99609.9e>). The SRDRN and UNet methods are implemented to optionally account for cyclical temporal patterns in case of spatio-temporal data. For more details of the methods, see Sipilä et al. (2025) <doi:10.48550/arXiv.2512.13753>.

r-smoothie 1.0-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=smoothie
Licenses: GPL 2+
Build system: r
Synopsis: Two-Dimensional Field Smoothing
Description:

Perform two-dimensional smoothing for spatial fields using FFT and the convolution theorem (see Gilleland 2013, <doi:10.5065/D61834G2>).

r-santar 1.2.4
Propagated dependencies: r-shiny@1.11.1 r-reshape2@1.4.5 r-plyr@1.8.9 r-pcamethods@2.2.0 r-iterators@1.0.14 r-gridextra@2.3 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dt@0.34.0 r-doparallel@1.0.17 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/adwolfer/santaR
Licenses: GPL 3
Build system: r
Synopsis: Short Asynchronous Time-Series Analysis
Description:

This package provides a graphical and automated pipeline for the analysis of short time-series in R ('santaR'). This approach is designed to accommodate asynchronous time sampling (i.e. different time points for different individuals), inter-individual variability, noisy measurements and large numbers of variables. Based on a smoothing splines functional model, santaR is able to detect variables highlighting significantly different temporal trajectories between study groups. Designed initially for metabolic phenotyping, santaR is also suited for other Systems Biology disciplines. Command line and graphical analysis (via a shiny application) enable fast and parallel automated analysis and reporting, intuitive visualisation and comprehensive plotting options for non-specialist users.

r-spreda 1.2
Propagated dependencies: r-survival@3.8-3 r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SPREDA
Licenses: GPL 2
Build system: r
Synopsis: Statistical Package for Reliability Data Analysis
Description:

The Statistical Package for REliability Data Analysis (SPREDA) implements recently-developed statistical methods for the analysis of reliability data. Modern technological developments, such as sensors and smart chips, allow us to dynamically track product/system usage as well as other environmental variables, such as temperature and humidity. We refer to these variables as dynamic covariates. The package contains functions for the analysis of time-to-event data with dynamic covariates and degradation data with dynamic covariates. The package also contains functions that can be used for analyzing time-to-event data with right censoring, and with left truncation and right censoring. Financial support from NSF and DuPont are acknowledged.

r-surveydefense 0.2.0
Propagated dependencies: r-flextable@0.9.10 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=SurveyDefense
Licenses: GPL 3
Build system: r
Synopsis: Survey Defense Tool
Description:

This tool is designed to analyze up to 5 Fraud Detection Questions integrated into a survey, focusing on potential fraudulent participants to clean the survey dataset from potential fraud. Fraud Detection Questions and further information available at <https://surveydefense.org>.

r-symphony 0.1.2
Propagated dependencies: r-uwot@0.2.4 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-rann@2.6.2 r-purrr@1.2.0 r-matrix@1.7-4 r-magrittr@2.0.4 r-irlba@2.3.5.1 r-harmony@1.2.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-class@7.3-23
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=symphony
Licenses: GPL 3+
Build system: r
Synopsis: Efficient and Precise Single-Cell Reference Atlas Mapping
Description:

This package implements the Symphony single-cell reference building and query mapping algorithms and additional functions described in Kang et al <https://www.nature.com/articles/s41467-021-25957-x>.

r-semaphore 1.2.0
Propagated dependencies: r-rcpp@1.1.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cmmr.github.io/semaphore/
Licenses: Expat
Build system: r
Synopsis: Shared Memory Atomic Operations
Description:

This package implements named semaphores from the boost C++ library <https://www.boost.org/> for interprocess communication. Multiple R sessions on the same host can block (with optional timeout) on a semaphore until it becomes positive, then atomically decrement it and unblock. Any session can increment the semaphore.

r-sciviews 0.9-13.2
Propagated dependencies: r-ellipse@0.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/SciViews/SciViews
Licenses: GPL 2
Build system: r
Synopsis: SciViews - Main package
Description:

This package provides functions to install SciViews additions to R, and more tools.

r-seqalignr 0.1.1
Propagated dependencies: r-plot-matrix@1.6.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SeqAlignR
Licenses: GPL 3
Build system: r
Synopsis: Sequence Alignment and Visualization Tool
Description:

Computes the optimal alignment of two character sequences. Visualizes the result of the alignment in a matrix plot. Needleman, Saul B.; Wunsch, Christian D. (1970) "A general method applicable to the search for similarities in the amino acid sequence of two proteins" <doi:10.1016/0022-2836(70)90057-4>.

r-streamdag 1.6
Propagated dependencies: r-plotrix@3.8-13 r-missforest@1.6.1 r-igraph@2.2.1 r-asbio@1.12-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=streamDAG
Licenses: GPL 2+
Build system: r
Synopsis: Analytical Methods for Stream DAGs
Description:

This package provides indices and tools for directed acyclic graphs (DAGs), particularly DAG representations of intermittent streams. A detailed introduction to the package can be found in the publication: "Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG" (Aho et al., 2023) <doi:10.1016/j.envsoft.2023.105775>, and in the introductory package vignette.

r-seasonal 1.10.0
Propagated dependencies: r-x13binary@1.1.61.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://www.seasonal.website
Licenses: GPL 3
Build system: r
Synopsis: R Interface to X-13-ARIMA-SEATS
Description:

Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. It offers full access to almost all options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model search, outlier detection and support for user defined holiday variables, such as Chinese New Year or Indian Diwali. A graphical user interface can be used through the seasonalview package. Uses the X-13-binaries from the x13binary package.

r-scornet 0.1.1
Propagated dependencies: r-survival@3.8-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-matrix@1.7-4 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/celehs/SCORNET
Licenses: GPL 3
Build system: r
Synopsis: Semi-Supervised Calibration of Risk with Noisy Event Times
Description:

This package provides a consistent, semi-supervised, non-parametric survival curve estimator optimized for efficient use of Electronic Health Record (EHR) data with a limited number of current status labels. See van der Laan and Robins (1997) <doi:10.2307/2670119>.

r-scitd 1.0.4
Propagated dependencies: r-sva@3.58.0 r-sccore@1.0.6 r-rtensor@1.4.9 r-rmisc@1.5.1 r-reshape2@1.4.5 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-nmf@0.28 r-msigdbr@25.1.1 r-mgcv@1.9-4 r-matrix@1.7-4 r-ica@1.0-3 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-fgsea@1.36.0 r-edger@4.8.0 r-dplyr@1.1.4 r-complexheatmap@2.26.0 r-circlize@0.4.16
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scITD
Licenses: GPL 3
Build system: r
Synopsis: Single-Cell Interpretable Tensor Decomposition
Description:

Single-cell Interpretable Tensor Decomposition (scITD) employs the Tucker tensor decomposition to extract multicell-type gene expression patterns that vary across donors/individuals. This tool is geared for use with single-cell RNA-sequencing datasets consisting of many source donors. The method has a wide range of potential applications, including the study of inter-individual variation at the population-level, patient sub-grouping/stratification, and the analysis of sample-level batch effects. Each "multicellular process" that is extracted consists of (A) a multi cell type gene loadings matrix and (B) a corresponding donor scores vector indicating the level at which the corresponding loadings matrix is expressed in each donor. Additional methods are implemented to aid in selecting an appropriate number of factors and to evaluate stability of the decomposition. Additional tools are provided for downstream analysis, including integration of gene set enrichment analysis and ligand-receptor analysis. Tucker, L.R. (1966) <doi:10.1007/BF02289464>. Unkel, S., Hannachi, A., Trendafilov, N. T., & Jolliffe, I. T. (2011) <doi:10.1007/s13253-011-0055-9>. Zhou, G., & Cichocki, A. (2012) <doi:10.2478/v10175-012-0051-4>.

r-swirl 2.4.5
Propagated dependencies: r-yaml@2.3.10 r-testthat@3.3.0 r-stringr@1.6.0 r-rcurl@1.98-1.17 r-httr@1.4.7 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://swirlstats.com
Licenses: Expat
Build system: r
Synopsis: Learn R, in R
Description:

Use the R console as an interactive learning environment. Users receive immediate feedback as they are guided through self-paced lessons in data science and R programming.

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