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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-shapleyoutlier 0.1.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-robustbase@0.99-6 r-rdpack@2.6.4 r-rcolorbrewer@1.1-3 r-magrittr@2.0.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-forcats@1.0.1 r-egg@0.4.5 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=ShapleyOutlier
Licenses: GPL 3
Synopsis: Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances
Description:

Based on Shapley values to explain multivariate outlyingness and to detect and impute cellwise outliers. Includes implementations of methods described in Mayrhofer and Filzmoser (2023) <doi:10.1016/j.ecosta.2023.04.003>.

r-spatialvs 1.1
Propagated dependencies: r-nlme@3.1-168 r-mass@7.3-65 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SpatialVS
Licenses: GPL 2
Synopsis: Spatial Variable Selection
Description:

Perform variable selection for the spatial Poisson regression model under the adaptive elastic net penalty. Spatial count data with covariates is the input. We use a spatial Poisson regression model to link the spatial counts and covariates. For maximization of the likelihood under adaptive elastic net penalty, we implemented the penalized quasi-likelihood (PQL) and the approximate penalized loglikelihood (APL) methods. The proposed methods can automatically select important covariates, while adjusting for possible spatial correlations among the responses. More details are available in Xie et al. (2018, <arXiv:1809.06418>). The package also contains the Lyme disease dataset, which consists of the disease case data from 2006 to 2011, and demographic data and land cover data in Virginia. The Lyme disease case data were collected by the Virginia Department of Health. The demographic data (e.g., population density, median income, and average age) are from the 2010 census. Land cover data were obtained from the Multi-Resolution Land Cover Consortium for 2006.

r-stdreg2 1.0.3
Propagated dependencies: r-survival@3.8-3 r-generics@0.1.4 r-drgee@1.1.10-3 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://sachsmc.github.io/stdReg2/
Licenses: AGPL 3+
Synopsis: Regression Standardization for Causal Inference
Description:

This package contains more modern tools for causal inference using regression standardization. Four general classes of models are implemented; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models, and shared frailty gamma-Weibull models. Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>. Also includes functionality for doubly robust estimation for generalized linear models in some special cases, and the ability to implement custom models.

r-stccgev 1.0.0
Propagated dependencies: r-rootsolve@1.8.2.4 r-ggplot2@4.0.1 r-evd@2.3-7.1 r-copula@1.1-6 r-bsts@0.9.11
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=STCCGEV
Licenses: Expat
Synopsis: Conditional Copula Model for Crop Yield Forecasting
Description:

This package provides functions to model and forecast crop yields using a spatial temporal conditional copula approach. The package incorporates extreme weather covariates and Bayesian Structural Time Series models to analyze crop yield dependencies across multiple regions. Includes tools for fitting, simulating, and visualizing results. This method build upon established R packages, including Hofert et al'. (2025) <doi:10.32614/CRAN.package.copula>, Scott (2024) <doi:10.32614/CRAN.package.bsts>, and Stephenson et al'. (2024) <doi:10.32614/CRAN.package.evd>.

r-standby 0.2.0
Propagated dependencies: r-shiny@1.11.1 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://standby.rsquaredacademy.com/
Licenses: GPL 3+
Synopsis: Alerts, Notifications and Loading Screen in 'Shiny'
Description:

Easily create alerts, notifications, modals, info tips and loading screens in Shiny'. Includes several options to customize alerts and notifications by including text, icons, images and buttons. When wrapped around a Shiny output, loading screen is automatically displayed while the output is being recalculated.

r-seecolor 0.2.0
Propagated dependencies: r-stringr@1.6.0 r-rstudioapi@0.17.1 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-fansi@1.0.7 r-dplyr@1.1.4 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/lovestat/seecolor
Licenses: Expat
Synopsis: View Colors Used in R Objects in the Console
Description:

Output colors used in literal vectors, palettes and plot objects (ggplot).

r-spinbayes 0.2.2
Propagated dependencies: r-testthat@3.3.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-glmnet@4.1-10 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jrhub/spinBayes
Licenses: GPL 2
Synopsis: Semi-Parametric Gene-Environment Interaction via Bayesian Variable Selection
Description:

Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Existing Bayesian methods for gene-environment (GÃ E) interaction studies are challenged by the high-dimensional nature of the study and the complexity of environmental influences. We have developed a novel and powerful semi-parametric Bayesian variable selection method that can accommodate linear and nonlinear GÃ E interactions simultaneously (Ren et al. (2020) <doi:10.1002/sim.8434>). Furthermore, the proposed method can conduct structural identification by distinguishing nonlinear interactions from main effects only case within Bayesian framework. Spike-and-slab priors are incorporated on both individual and group level to shrink coefficients corresponding to irrelevant main and interaction effects to zero exactly. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++.

r-squid 0.2.1
Propagated dependencies: r-shinymatrix@0.8.0 r-shiny@1.11.1 r-plotly@4.11.0 r-mass@7.3-65 r-lme4@1.1-37 r-ggplot2@4.0.1 r-data-table@1.17.8 r-brms@2.23.0 r-arm@1.14-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/squid-group/squid
Licenses: Expat
Synopsis: Statistical Quantification of Individual Differences
Description:

This package provides a simulation-based tool made to help researchers to become familiar with multilevel variations, and to build up sampling designs for their study. This tool has two main objectives: First, it provides an educational tool useful for students, teachers and researchers who want to learn to use mixed-effects models. Users can experience how the mixed-effects model framework can be used to understand distinct biological phenomena by interactively exploring simulated multilevel data. Second, it offers research opportunities to those who are already familiar with mixed-effects models, as it enables the generation of data sets that users may download and use for a range of simulation-based statistical analyses such as power and sensitivity analysis of multilevel and multivariate data [Allegue, H., Araya-Ajoy, Y.G., Dingemanse, N.J., Dochtermann N.A., Garamszegi, L.Z., Nakagawa, S., Reale, D., Schielzeth, H. and Westneat, D.F. (2016) <doi: 10.1111/2041-210X.12659>].

r-shinymixr 0.5.3
Propagated dependencies: r-xfun@0.54 r-whisker@0.4.1 r-stringi@1.8.7 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shinyace@0.4.4 r-shiny@1.11.1 r-rxode2@5.0.1 r-r3port@0.3.1 r-ps@1.9.1 r-plotly@4.11.0 r-patchwork@1.3.2 r-nlmixr2est@5.0.2 r-magrittr@2.0.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-fresh@0.2.2 r-dt@0.34.0 r-collapsibletree@0.1.8 r-cli@3.6.5 r-bs4dash@2.3.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/RichardHooijmaijers/shinyMixR/
Licenses: Expat
Synopsis: Interactive 'shiny' Dashboard for 'nlmixr2'
Description:

An R shiny user interface for the nlmixr2 (Fidler et al (2019) <doi:10.1002/psp4.12445>) package, designed to simplify the modeling process for users. Additionally, this package includes supplementary functions to further enhances the usage of nlmixr2'.

r-socialrisk 0.5.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/WYATTBENSKEN/multimorbidity
Licenses: Expat
Synopsis: Identifying Patient Social Risk from Administrative Health Care Data
Description:

Social risks are increasingly becoming a critical component of health care research. One of the most common ways to identify social needs is by using ICD-10-CM "Z-codes." This package identifies social risks using varying taxonomies of ICD-10-CM Z-codes from administrative health care data. The conceptual taxonomies come from: Centers for Medicare and Medicaid Services (2021) <https://www.cms.gov/files/document/zcodes-infographic.pdf>, Reidhead (2018) <https://web.mhanet.com/>, A Arons, S DeSilvey, C Fichtenberg, L Gottlieb (2018) <https://sirenetwork.ucsf.edu/tools-resources/resources/compendium-medical-terminology-codes-social-risk-factors>.

r-sleekts 1.0.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sleekts
Licenses: GPL 3
Synopsis: 4253H, Twice Smoothing
Description:

Compute Time series Resistant Smooth 4253H, twice smoothing method.

r-sewage 0.2.5
Propagated dependencies: r-glue@1.8.0 r-diagrammer@1.0.11 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mwhalen18/sewage
Licenses: Expat
Synopsis: Light-Weight Data Pipelining Tool
Description:

This package provides a simple interface to developing complex data pipelines which can be executed in a single call. sewage makes it easy to test, debug, and share data pipelines through it's interface and visualizations.

r-segcorr 1.2
Propagated dependencies: r-jointseg@1.0.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SegCorr
Licenses: GPL 2
Synopsis: Detecting Correlated Genomic Regions
Description:

This package performs correlation matrix segmentation and applies a test procedure to detect highly correlated regions in gene expression.

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
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-soil 1.1
Propagated dependencies: r-ncvreg@3.16.0 r-mass@7.3-65 r-glmnet@4.1-10 r-brglm2@1.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/emeryyi/SOIL
Licenses: GPL 2
Synopsis: Sparsity Oriented Importance Learning
Description:

Sparsity Oriented Importance Learning (SOIL) provides a new variable importance measure for high dimensional linear regression and logistic regression from a sparse penalization perspective, by taking into account the variable selection uncertainty via the use of a sensible model weighting. The package is an implementation of Ye, C., Yang, Y., and Yang, Y. (2017+).

r-spinyreg 0.1-0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spinyReg
Licenses: GPL 2+
Synopsis: Sparse Generative Model and Its EM Algorithm
Description:

This package implements a generative model that uses a spike-and-slab like prior distribution obtained by multiplying a deterministic binary vector. Such a model allows an EM algorithm, optimizing a type-II log-likelihood.

r-shinyfilter 0.1.1
Propagated dependencies: r-stringr@1.6.0 r-shinyjs@2.1.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-reactable@0.4.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jsugarelli/shinyfilter/
Licenses: GPL 3
Synopsis: Use Interdependent Filters on Table Columns in Shiny Apps
Description:

Allows to connect selectizeInputs widgets as filters to a reactable table. As known from spreadsheet applications, column filters are interdependent, so each filter only shows the values that are really available at the moment based on the current selection in other filters. Filter values currently not available (and also those being available) can be shown via popovers or tooltips.

r-soptdmaea 1.0.1
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=soptdmaeA
Licenses: GPL 2
Synopsis: Sequential Optimal Designs for Two-Colour cDNA Microarray Experiments
Description:

Computes sequential A-, MV-, D- and E-optimal or near-optimal block and row-column designs for two-colour cDNA microarray experiments using the linear fixed effects and mixed effects models where the interest is in a comparison of all possible elementary treatment contrasts. The package also provides an optional method of using the graphical user interface (GUI) R package tcltk to ensure that it is user friendly.

r-ssgl 2.0
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-grpreg@3.5.0 r-gigrvg@0.8 r-foreach@1.5.2 r-dorng@1.8.6.2 r-doparallel@1.0.17 r-caret@7.0-1 r-bayeslogit@2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SSGL
Licenses: GPL 3
Synopsis: Spike-and-Slab Group Lasso for Group-Regularized Generalized Linear Models
Description:

Fits group-regularized generalized linear models (GLMs) using the spike-and-slab group lasso (SSGL) prior of Bai et al. (2022) <doi:10.1080/01621459.2020.1765784> and extended to GLMs by Bai (2023) <doi:10.48550/arXiv.2007.07021>. This package supports fitting the SSGL model for the following GLMs with group sparsity: Gaussian linear regression, binary logistic regression, and Poisson regression.

r-spqdep 0.1.3.6
Propagated dependencies: r-units@1.0-0 r-tidyr@1.3.1 r-spdep@1.4-1 r-spatialreg@1.4-2 r-sp@2.2-0 r-sf@1.0-23 r-rsample@1.3.1 r-purrr@1.2.0 r-matrix@1.7-4 r-magrittr@2.0.4 r-igraph@2.2.1 r-gtools@3.9.5 r-gt@1.2.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://f8l5h9.github.io/spqdep/
Licenses: Expat
Synopsis: Testing for Spatial Independence of Cross-Sectional Qualitative Data
Description:

Testing for Spatial Dependence of Qualitative Data in Cross Section. The list of functions includes join-count tests, Q test, spatial scan test, similarity test and spatial runs test. The methodology of these models can be found in <doi:10.1007/s10109-009-0100-1> and <doi:10.1080/13658816.2011.586327>.

r-svsweave 1.0.0
Propagated dependencies: r-rmarkdown@2.30 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/SciViews/svSweave
Licenses: GPL 2
Synopsis: 'SciViews' - 'Sweave', 'Knitr' and R Markdown Companion Functions
Description:

This package provides functions to enumerate and reference figures, tables and equations in R Markdown documents that do not support these features (thus not bookdown or quarto'. Supporting functions for using Sweave and Knitr with LyX'.

r-sqliteutils 0.1.0
Propagated dependencies: r-rsqlite@2.4.4 r-magrittr@2.0.4 r-dplyr@1.1.4 r-dbplyr@2.5.1 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=sqliteutils
Licenses: Expat
Synopsis: Utility Functions for 'SQLite'
Description:

This package provides a tool for working with SQLite databases. SQLite has some idiosyncrasies and limitations that impose some hurdles to the R developer who is using this database as a repository. For instance, SQLite doesn't have a date type and sqliteutils has some functions to deal with that.

r-statgenibd 1.0.9
Propagated dependencies: r-stringi@1.8.7 r-statgengwas@1.0.12 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r-utils@2.13.0 r-matrix@1.7-4 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://biometris.github.io/statgenIBD/index.html
Licenses: GPL 2+ GPL 3+
Synopsis: Calculation of IBD Probabilities
Description:

For biparental, three and four-way crosses Identity by Descent (IBD) probabilities can be calculated using Hidden Markov Models and inheritance vectors following Lander and Green (<https://www.jstor.org/stable/29713>) and Huang (<doi:10.1073/pnas.1100465108>). One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.

r-statnipokladna 0.7.7
Propagated dependencies: r-xml2@1.5.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 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-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 r-curl@7.0.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/petrbouchal/statnipokladna
Licenses: Expat
Synopsis: Use Data from the Czech Public Finance Database
Description:

Get programmatic access to data from the Czech public budgeting and accounting database, Státnà pokladna <https://monitor.statnipokladna.gov.cz/>.

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