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    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
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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-svyvgam 1.3
Propagated dependencies: r-vgam@1.1-13 r-survey@4.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=svyVGAM
Licenses: GPL 3
Build system: r
Synopsis: Design-Based Inference in Vector Generalised Linear Models
Description:

This package provides inference based on the survey package for the wide range of parametric models in the VGAM package.

r-stabilizedregression 1.1
Propagated dependencies: r-r6@2.6.1 r-mass@7.3-65 r-glmnet@4.1-10 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=StabilizedRegression
Licenses: GPL 3
Build system: r
Synopsis: Stabilizing Regression and Variable Selection
Description:

This package contains an implementation of StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2021) <arXiv:1911.01850>. The procedure uses averaging to estimate a regression of a set of predictors X on a response variable Y by enforcing stability with respect to a given environment variable. The resulting regression leads to a variable selection procedure which allows to distinguish between stable and unstable predictors. The package further implements a visualization technique which illustrates the trade-off between stability and predictiveness of individual predictors.

r-simstatespace 1.2.15
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jeksterslab/simStateSpace
Licenses: GPL 3+
Build system: r
Synopsis: Simulate Data from State Space Models
Description:

This package provides a streamlined and user-friendly framework for simulating data in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. This package was designed to generate data for the simulations performed in Pesigan, Russell, and Chow (2025) <doi:10.1037/met0000779>.

r-scr 0.4.0
Propagated dependencies: r-tidyr@1.3.1 r-plotly@4.11.0 r-pbapply@1.7-4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/pjesscarter/scR
Licenses: Expat
Build system: r
Synopsis: Estimate Vapnik-Chervonenkis Dimension and Sample Complexity
Description:

We provide a suite of tools for estimating the sample complexity of a chosen model through theoretical bounds and simulation. The package incorporates methods for estimating the Vapnik-Chervonenkis dimension (VCD) of a chosen algorithm, which can be used to estimate its sample complexity. Alternatively, we provide simulation methods to estimate sample complexity directly. For more details, see Carter, P & Choi, D (2024). "Learning from Noise: Applying Sample Complexity for Political Science Research" <doi:10.31219/osf.io/evrcj>.

r-sdmtune 1.3.3
Dependencies: openjdk@25
Propagated dependencies: r-whisker@0.4.1 r-terra@1.8-86 r-stringr@1.6.0 r-rstudioapi@0.17.1 r-rlang@1.1.6 r-rcpp@1.1.0 r-randomforest@4.7-1.2 r-nnet@7.3-20 r-maxnet@0.1.4 r-jsonlite@2.0.0 r-ggplot2@4.0.1 r-gbm@2.2.2 r-dismo@1.3-16 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://consbiol-unibern.github.io/SDMtune/
Licenses: GPL 3
Build system: r
Synopsis: Species Distribution Model Selection
Description:

User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the RStudio viewer pane during their execution.

r-sadisa 1.2
Propagated dependencies: r-pracma@2.4.6 r-ddd@5.2.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SADISA
Licenses: GPL 3
Build system: r
Synopsis: Species Abundance Distributions with Independent-Species Assumption
Description:

Computes the probability of a set of species abundances of a single or multiple samples of individuals with one or more guilds under a mainland-island model. One must specify the mainland (metacommunity) model and the island (local) community model. It assumes that species fluctuate independently. The package also contains functions to simulate under this model. See Haegeman, B. & R.S. Etienne (2017). A general sampling formula for community structure data. Methods in Ecology & Evolution 8: 1506-1519 <doi:10.1111/2041-210X.12807>.

r-statcomp 0.1.0
Propagated dependencies: r-zoo@1.8-14 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=statcomp
Licenses: GPL 2
Build system: r
Synopsis: Statistical Complexity and Information Measures for Time Series Analysis
Description:

An implementation of local and global statistical complexity measures (aka Information Theory Quantifiers, ITQ) for time series analysis based on ordinal statistics (Bandt and Pompe (2002) <DOI:10.1103/PhysRevLett.88.174102>). Several distance measures that operate on ordinal pattern distributions, auxiliary functions for ordinal pattern analysis, and generating functions for stochastic and deterministic-chaotic processes for ITQ testing are provided.

r-snpaimer 2.1.1
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-tidyr@1.3.1 r-readr@2.1.6 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-foreach@1.5.2 r-forcats@1.0.1 r-dplyr@1.1.4 r-doparallel@1.0.17 r-adegenet@2.1.11
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/OksanaVe/snpAIMeR
Licenses: Expat
Build system: r
Synopsis: Assess the Diagnostic Power of Genomic Marker Combinations
Description:

Population genetics package for designing diagnostic panels. Candidate markers, marker combinations, and different panel sizes are assessed for how well they can predict the source population of known samples. Requires a genotype file of candidate markers in STRUCTURE format. Methods for population cross-validation are described in Jombart (2008) <doi:10.1093/bioinformatics/btn129>.

r-seuratexplorer 0.1.2
Propagated dependencies: r-shinywidgets@0.9.0 r-shinyjqui@0.4.1 r-shinydashboardplus@2.0.6 r-shinydashboard@0.7.3 r-shinycssloaders@1.1.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-seuratobject@5.2.0 r-seurat@5.3.1 r-scales@1.4.0 r-reshape2@1.4.5 r-qs2@0.1.6 r-patchwork@1.3.2 r-markdown@2.0 r-knitr@1.50 r-ggplot2@4.0.1 r-ggalluvial@0.12.5 r-dt@0.34.0 r-dplyr@1.1.4 r-colourpicker@1.3.0 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=SeuratExplorer
Licenses: GPL 3+
Build system: r
Synopsis: An 'Shiny' App for Exploring scRNA-seq Data Processed in 'Seurat'
Description:

This package provides a simple, one-command package which runs an interactive dashboard capable of common visualizations for single cell RNA-seq. SeuratExplorer requires a processed Seurat object, which is saved as rds or qs2 file.

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.

r-skiftitools 0.1.0
Propagated dependencies: r-stringr@1.6.0 r-s2dv@2.2.1 r-rvcg@0.25 r-rnifti@1.8.0 r-rmarchingcubes@0.1.4 r-rgl@1.3.31 r-r-utils@2.13.0 r-png@0.1-8 r-oce@1.8-3 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/haanme/skiftiTools
Licenses: GPL 3
Build system: r
Synopsis: Tools and Operations for Reading, Writing, Viewing, and Manipulating SKIFTI Files
Description:

SKIFTI files contain brain imaging data in coordinates across Tract Based Spatial Statistics (TBSS) skeleton, which represent the brain white matter intensity values. skiftiTools provides a unified environment for reading, writing, visualizing and manipulating SKIFTI-format data. It supports the "subsetting", "concatenating", and using data as data.frame for R statistical functions. The SKIFTI data is structured for convenient access to the data and metadata, and includes support for visualizations. For more information see Merisaari et al. (2024) <doi:10.57736/87d2-0608>.

r-seqicp 1.1
Propagated dependencies: r-mgcv@1.9-4 r-dhsic@2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=seqICP
Licenses: GPL 3
Build system: r
Synopsis: Sequential Invariant Causal Prediction
Description:

This package contains an implementation of invariant causal prediction for sequential data. The main function in the package is seqICP', which performs linear sequential invariant causal prediction and has guaranteed type I error control. For non-linear dependencies the package also contains a non-linear method seqICPnl', which allows to input any regression procedure and performs tests based on a permutation approach that is only approximately correct. In order to test whether an individual set S is invariant the package contains the subroutines seqICP.s and seqICPnl.s corresponding to the respective main methods.

r-simmer-plot 0.1.19
Propagated dependencies: r-tidyr@1.3.1 r-simmer@4.4.7 r-scales@1.4.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-diagrammer@1.0.11
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://r-simmer.org
Licenses: Expat
Build system: r
Synopsis: Plotting Methods for 'simmer'
Description:

This package provides a set of plotting methods for simmer trajectories and simulations.

r-spdgp 0.1.0
Propagated dependencies: r-vctrs@0.6.5 r-spdep@1.4-1 r-spatialreg@1.4-2 r-smoothmest@0.1-3 r-sf@1.0-23 r-rlang@1.1.6 r-matrix@1.7-4 r-mass@7.3-65 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://josiahparry.github.io/spdgp/
Licenses: Expat
Build system: r
Synopsis: Simulate Spatial Data Generation Processes
Description:

This package provides functionality for simulating data generation processes across various spatial regression models, conceptually aligned with the dgp module of the Python library spreg <https://pysal.org/spreg/api.html#dgp>.

r-shazam 1.3.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringi@1.8.7 r-seqinr@4.2-36 r-scales@1.4.0 r-rlang@1.1.6 r-progress@1.2.3 r-mass@7.3-65 r-lazyeval@0.2.2 r-kernsmooth@2.23-26 r-iterators@1.0.14 r-igraph@2.2.1 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-diptest@0.77-2 r-ape@5.8-1 r-alakazam@1.4.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://shazam.readthedocs.io
Licenses: AGPL 3
Build system: r
Synopsis: Immunoglobulin Somatic Hypermutation Analysis
Description:

This package provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.

r-seahors 1.9.0
Propagated dependencies: r-viridis@0.6.5 r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-rmarkdown@2.30 r-readxl@1.4.5 r-raster@3.6-32 r-plotly@4.11.0 r-mass@7.3-65 r-htmlwidgets@1.6.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/AurelienRoyer/SEAHORS
Licenses: GPL 3
Build system: r
Synopsis: Spatial Exploration of ArcHaeological Objects in R Shiny
Description:

An R Shiny application dedicated to the intra-site spatial analysis of piece-plotted archaeological remains, making the two and three-dimensional spatial exploration of archaeological data as user-friendly as possible. Documentation about SEAHORS is provided by the vignette included in this package and by the companion scientific paper: Royer, Discamps, Plutniak, Thomas (2023, PCI Archaeology, <doi:10.5281/zenodo.7674698>).

r-sdaresources 0.1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SDAResources
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Datasets and Functions for 'Sampling: Design and Analysis, 3rd Edition'
Description:

Includes all the datasets of Sampling: Design and Analysis (3rd edition by Sharon Lohr) in R format and additional functions for analyzing and graphing probability samples.

r-surf-vs 1.1.0.1
Propagated dependencies: r-survival@3.8-3 r-glmnet@4.1-10 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=SuRF.vs
Licenses: GPL 3
Build system: r
Synopsis: Subsampling Ranking Forward Selection (SuRF)
Description:

This package performs variable selection based on subsampling, ranking forward selection. Details of the method are published in Lihui Liu, Hong Gu, Johan Van Limbergen, Toby Kenney (2020) SuRF: A new method for sparse variable selection, with application in microbiome data analysis Statistics in Medicine 40 897-919 <doi:10.1002/sim.8809>. Xo is the matrix of predictor variables. y is the response variable. Currently only binary responses using logistic regression are supported. X is a matrix of additional predictors which should be scaled to have sum 1 prior to analysis. fold is the number of folds for cross-validation. Alpha is the parameter for the elastic net method used in the subsampling procedure: the default value of 1 corresponds to LASSO. prop is the proportion of variables to remove in the each subsample. weights indicates whether observations should be weighted by class size. When the class sizes are unbalanced, weighting observations can improve results. B is the number of subsamples to use for ranking the variables. C is the number of permutations to use for estimating the critical value of the null distribution. If the doParallel package is installed, the function can be run in parallel by setting ncores to the number of threads to use. If the default value of 1 is used, or if the doParallel package is not installed, the function does not run in parallel. display.progress indicates whether the function should display messages indicating its progress. family is a family variable for the glm() fitting. Note that the glmnet package does not permit the use of nonstandard link functions, so will always use the default link function. However, the glm() fitting will use the specified link. The default is binomial with logistic regression, because this is a common use case. pval is the p-value for inclusion of a variable in the model. Under the null case, the number of false positives will be geometrically distributed with this as probability of success, so if this parameter is set to p, the expected number of false positives should be p/(1-p).

r-shinyrgl 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-rgl@1.3.31
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shinyRGL
Licenses: Expat
Build system: r
Synopsis: Shiny Wrappers for RGL
Description:

Shiny wrappers for the RGL package. This package exposes RGL's ability to export WebGL visualization in a shiny-friendly format.

r-sqlstrings 1.0.0
Propagated dependencies: r-stringr@1.6.0 r-readr@2.1.6 r-fs@1.6.6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sqlstrings
Licenses: Expat
Build system: r
Synopsis: Map 'SQL' Code to R Lists
Description:

This package provides a helper function, to bulk read SQL code from separate files and load it into an R list, where the list elements contain the individual statements and queries as strings. This works by annotating the SQL code with a name comment, which also will be the name of the list element.

r-salty 0.1.2
Propagated dependencies: r-stringr@1.6.0 r-purrr@1.2.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mdlincoln/salty
Licenses: Expat
Build system: r
Synopsis: Turn Clean Data into Messy Data
Description:

Take real or simulated data and salt it with errors commonly found in the wild, such as pseudo-OCR errors, Unicode problems, numeric fields with nonsensical punctuation, bad dates, etc.

r-spotifyr 2.2.5
Propagated dependencies: r-xml2@1.5.0 r-tibble@3.3.0 r-stringr@1.6.0 r-rvest@1.0.5 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-janitor@2.2.1 r-httr@1.4.7 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/charlie86/spotifyr
Licenses: Expat
Build system: r
Synopsis: R Wrapper for the 'Spotify' Web API
Description:

An R wrapper for pulling data from the Spotify Web API <https://developer.spotify.com/documentation/web-api/> in bulk, or post items on a Spotify user's playlist.

r-swimplot 1.2.0
Propagated dependencies: r-tidyr@1.3.1 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=swimplot
Licenses: GPL 3
Build system: r
Synopsis: Tools for Creating Swimmers Plots using 'ggplot2'
Description:

Used for creating swimmers plots with functions to customize the bars, add points, add lines, add text, and add arrows.

r-soiltestcorr 2.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://adriancorrendo.github.io/soiltestcorr/
Licenses: Expat
Build system: r
Synopsis: Soil Test Correlation and Calibration
Description:

This package provides a compilation of functions designed to assist users on the correlation analysis of crop yield and soil test values. Functions to estimate crop response patterns to soil nutrient availability and critical soil test values using various approaches such as: 1) the modified arcsine-log calibration curve (Correndo et al. (2017) <doi:10.1071/CP16444>); 2) the graphical Cate-Nelson quadrants analysis (Cate & Nelson (1965)), 3) the statistical Cate-Nelson quadrants analysis (Cate & Nelson (1971) <doi:10.2136/sssaj1971.03615995003500040048x>), 4) the linear-plateau regression (Anderson & Nelson (1975) <doi:10.2307/2529422>), 5) the quadratic-plateau regression (Bullock & Bullock (1994) <doi:10.2134/agronj1994.00021962008600010033x>), and 6) the Mitscherlich-type exponential regression (Melsted & Peck (1977) <doi:10.2134/asaspecpub29.c1>). The package development stemmed from ongoing work with the Fertilizer Recommendation Support Tool (FRST) and Feed the Future Innovation Lab for Collaborative Research on Sustainable Intensification (SIIL) projects.

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