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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-ggeda 0.2.0
Propagated dependencies: r-scales@1.4.0 r-rlang@1.1.6 r-rank@0.2.0 r-patchwork@1.3.2 r-ggtext@0.1.2 r-ggplot2@4.0.1 r-ggiraph@0.9.2 r-cli@3.6.5 r-assertions@0.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/CCICB/ggEDA
Licenses: Expat
Build system: r
Synopsis: Turnkey Visualisations for Exploratory Data Analysis
Description:

This package provides interactive visualisations for exploratory data analysis of high-dimensional datasets. Includes parallel coordinate plots for exploring large datasets with mostly quantitative features, but also stacked one-dimensional visualisations that more effectively show missingness and complex categorical relationships in smaller datasets.

r-geofi 1.1.0
Propagated dependencies: r-yaml@2.3.10 r-xml2@1.5.0 r-sf@1.0-23 r-rlang@1.1.6 r-purrr@1.2.0 r-jsonlite@2.0.0 r-httr2@1.2.1 r-httr@1.4.7 r-httpcache@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://ropengov.github.io/geofi/
Licenses: FreeBSD
Build system: r
Synopsis: Access Finnish Geospatial Data
Description:

Designed to simplify geospatial data access from the Statistics Finland Web Feature Service API <https://geo.stat.fi/geoserver/index.html>, the geofi package offers researchers and analysts a set of tools to obtain and harmonize administrative spatial data for a wide range of applications, from urban planning to environmental research. The package contains annually updated time series of municipality key datasets that can be used for data aggregation and language translations.

r-ggdensity 1.0.0
Propagated dependencies: r-vctrs@0.6.5 r-tibble@3.3.0 r-scales@1.4.0 r-mass@7.3-65 r-isoband@0.2.7 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://jamesotto852.github.io/ggdensity/
Licenses: Expat
Build system: r
Synopsis: Interpretable Bivariate Density Visualization with 'ggplot2'
Description:

The ggplot2 package provides simple functions for visualizing contours of 2-d kernel density estimates. ggdensity implements several additional density estimators as well as more interpretable visualizations based on highest density regions instead of the traditional height of the estimated density surface.

r-gausscov 1.1.8
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gausscov
Licenses: GPL 3
Build system: r
Synopsis: The Gaussian Covariate Method for Variable Selection
Description:

The standard linear regression theory whether frequentist or Bayesian is based on an assumed (revealed?) truth (John Tukey) attitude to models. This is reflected in the language of statistical inference which involves a concept of truth, for example confidence intervals, hypothesis testing and consistency. The motivation behind this package was to remove the word true from the theory and practice of linear regression and to replace it by approximation. The approximations considered are the least squares approximations. An approximation is called valid if it contains no irrelevant covariates. This is operationalized using the concept of a Gaussian P-value which is the probability that pure Gaussian noise is better in term of least squares than the covariate. The precise definition given in the paper "An Approximation Based Theory of Linear Regression". Only four simple equations are required. Moreover the Gaussian P-values can be simply derived from standard F P-values. Furthermore they are exact and valid whatever the data in contrast F P-values are only valid for specially designed simulations. A valid approximation is one where all the Gaussian P-values are less than a threshold p0 specified by the statistician, in this package with the default value 0.01. This approximations approach is not only much simpler it is overwhelmingly better than the standard model based approach. The will be demonstrated using high dimensional regression and vector autoregression real data sets. The goal is to find valid approximations. The search function is f1st which is a greedy forward selection procedure which results in either just one or no approximations which may however not be valid. If the size is less than than a threshold with default value 21 then an all subset procedure is called which returns the best valid subset. A good default start is f1st(y,x,kmn=15) The best function for returning multiple approximations is f3st which repeatedly calls f1st. For more information see the papers: L. Davies and L. Duembgen, "Covariate Selection Based on a Model-free Approach to Linear Regression with Exact Probabilities", <doi:10.48550/arXiv.2202.01553>, L. Davies, "An Approximation Based Theory of Linear Regression", 2024, <doi:10.48550/arXiv.2402.09858>.

r-gamselbayes 2.0-3
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gamselBayes
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Generalized Additive Model Selection
Description:

Generalized additive model selection via approximate Bayesian inference is provided. Bayesian mixed model-based penalized splines with spike-and-slab-type coefficient prior distributions are used to facilitate fitting and selection. The approximate Bayesian inference engine options are: (1) Markov chain Monte Carlo and (2) mean field variational Bayes. Markov chain Monte Carlo has better Bayesian inferential accuracy, but requires a longer run-time. Mean field variational Bayes is faster, but less accurate. The methodology is described in He and Wand (2024) <doi:10.1007/s10182-023-00490-y>.

r-gutenbergr 0.4.1
Propagated dependencies: r-urltools@1.7.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-readmdtable@0.3.2 r-purrr@1.2.0 r-glue@1.8.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://docs.ropensci.org/gutenbergr/
Licenses: GPL 2
Build system: r
Synopsis: Download and Process Public Domain Works from Project Gutenberg
Description:

Download and process public domain works in the Project Gutenberg collection <https://www.gutenberg.org/>. Includes metadata for all Project Gutenberg works, so that they can be searched and retrieved.

r-gmvjoint 0.4.5
Propagated dependencies: r-xtable@1.8-4 r-survival@3.8-3 r-statmod@1.5.1 r-reformulas@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-mvtnorm@1.3-3 r-mass@7.3-65 r-glmmtmb@1.1.13
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/jamesmurray7/gmvjoint
Licenses: GPL 3
Build system: r
Synopsis: Joint Models of Survival and Multivariate Longitudinal Data
Description:

Fit joint models of survival and multivariate longitudinal data. The longitudinal data is specified by generalised linear mixed models. The joint models are fit via maximum likelihood using an approximate expectation maximisation algorithm. Bernhardt (2015) <doi:10.1016/j.csda.2014.11.011>.

r-gofar 0.1
Propagated dependencies: r-rrpack@0.1-14 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mass@7.3-65 r-magrittr@2.0.4 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/amishra-stats/gofar
Licenses: GPL 3+
Build system: r
Synopsis: Generalized Co-Sparse Factor Regression
Description:

Divide and conquer approach for estimating low-rank and sparse coefficient matrix in the generalized co-sparse factor regression. Please refer the manuscript Mishra, Aditya, Dipak K. Dey, Yong Chen, and Kun Chen. Generalized co-sparse factor regression. Computational Statistics & Data Analysis 157 (2021): 107127 for more details.

r-gomp 1.0
Propagated dependencies: r-survival@3.8-3 r-rfast2@0.1.5.5 r-rfast@2.1.5.2 r-quantreg@6.1 r-ordinal@2023.12-4.1 r-nnet@7.3-20 r-mass@7.3-65 r-hmisc@5.2-4 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gomp
Licenses: GPL 2+
Build system: r
Synopsis: The gamma-OMP Feature Selection Algorithm
Description:

The gamma-Orthogonal Matching Pursuit (gamma-OMP) is a recently suggested modification of the OMP feature selection algorithm for a wide range of response variables. The package offers many alternative regression models, such linear, robust, survival, multivariate etc., including k-fold cross-validation. References: Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2018). "Efficient feature selection on gene expression data: Which algorithm to use?" BioRxiv. <doi:10.1101/431734>. Tsagris M., Papadovasilakis Z., Lakiotaki K. and Tsamardinos I. (2022). "The gamma-OMP algorithm for feature selection with application to gene expression data". IEEE/ACM Transactions on Computational Biology and Bioinformatics 19(2): 1214--1224. <doi:10.1109/TCBB.2020.3029952>.

r-gitlink 0.1.3
Propagated dependencies: r-rlang@1.1.6 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/colearendt/gitlink
Licenses: Expat
Build system: r
Synopsis: Add 'Git' Links to Your Web Based Assets
Description:

This package provides helpers to add Git links to shiny applications, rmarkdown documents, and other HTML based resources. This is most commonly used for GitHub ribbons.

r-ggebiplots 0.1.3
Propagated dependencies: r-scales@1.4.0 r-ggplot2@4.0.1 r-ggforce@0.5.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GGEBiplots
Licenses: GPL 3
Build system: r
Synopsis: GGE Biplots with 'ggplot2'
Description:

Genotype plus genotype-by-environment (GGE) biplots rendered using ggplot2'. Provides a command line interface to all of the functionality contained within the archived package GGEBiplotGUI'.

r-geopsych 0.1.0
Propagated dependencies: r-sp@2.2-0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/ZhangSui921/geopsych
Licenses: GPL 3+
Build system: r
Synopsis: Methods of Applied Psychology and Psychometrics in Geographical Analysis
Description:

Integrating applied psychological and psychometric methods into geographical analysis. With the emergence of geo-referenced questionnaires, spatially explicit psychological and psychometric methods can offer a geographically contextualised approach that reflects latent traits and processes at a more local scale, leading to more tailored research and decision-making processes. The implemented methods include Geographically Weighted Cronbach's alpha and its bandwidth selection. See Zhang & Li (2025) <doi:10.1111/gean.70021>.

r-genpathmox 1.1
Propagated dependencies: r-matrixcalc@1.0-6 r-diagram@1.6.5 r-csem@0.6.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=genpathmox
Licenses: GPL 3
Build system: r
Synopsis: Pathmox Approach Segmentation Tree Analysis
Description:

It provides an interesting solution for handling a high number of segmentation variables in partial least squares structural equation modeling. The package implements the "Pathmox" algorithm (Lamberti, Sanchez, and Aluja,(2016)<doi:10.1002/asmb.2168>) including the F-coefficient test (Lamberti, Sanchez, and Aluja,(2017)<doi:10.1002/asmb.2270>) to detect the path coefficients responsible for the identified differences). The package also allows running the hybrid multi-group approach (Lamberti (2021) <doi:10.1007/s11135-021-01096-9>).

r-goodpractice 1.0.5
Propagated dependencies: r-xmlparsedata@1.0.5 r-xml2@1.5.0 r-withr@3.0.2 r-whoami@1.3.0 r-rstudioapi@0.17.1 r-rcmdcheck@1.4.0 r-praise@1.0.0 r-lintr@3.3.0-1 r-jsonlite@2.0.0 r-desc@1.4.3 r-cyclocomp@1.1.1 r-crayon@1.5.3 r-covr@3.6.5 r-clisymbols@1.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://docs.ropensci.org/goodpractice/
Licenses: Expat
Build system: r
Synopsis: Advice on R Package Building
Description:

Give advice about good practices when building R packages. Advice includes functions and syntax to avoid, package structure, code complexity, code formatting, etc.

r-gctensor 1.0.0
Propagated dependencies: r-rtensor@1.4.9 r-einsum@0.1.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/rikenbit/gcTensor
Licenses: Expat
Build system: r
Synopsis: Generalized Coupled Tensor Factorization
Description:

Multiple matrices/tensors can be specified and decomposed simultaneously by Probabilistic Latent Tensor Factorisation (PLTF). See the reference section of GitHub README.md <https://github.com/rikenbit/gcTensor>, for details of the method.

r-glmfitmiss 2.1.0
Propagated dependencies: r-mass@7.3-65 r-dplyr@1.1.4 r-data-table@1.17.8 r-brglm2@1.0.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=glmfitmiss
Licenses: Expat
Build system: r
Synopsis: Fitting GLMs with Missing Data in Both Responses and Covariates
Description:

Fits generalized linear models (GLMs) when there is missing data in both the response and categorical covariates. The functions implement likelihood-based methods using the Expectation and Maximization (EM) algorithm and optionally apply Firthâ s bias correction for improved inference. See Pradhan, Nychka, and Bandyopadhyay (2025) <https:>, Maiti and Pradhan (2009) <doi:10.1111/j.1541-0420.2008.01186.x>, Maity, Pradhan, and Das (2019) <doi:10.1080/00031305.2017.1407359> for further methodological details.

r-gvcanalyzer 0.1.1
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gvcAnalyzer
Licenses: Expat
Build system: r
Synopsis: Global Value Chain Decomposition for Value-Added Trade
Description:

This package provides tools for decomposing Global Value Chain (GVC) participation and value-added trade. It implements the frameworks proposed by Borin and Mancini (2023) 10.1080/09535314.2022.2153221> for source-based and sink-based decompositions, and by Borin, Mancini, and Taglioni (2025) 10.1093/wber/lhaf017> for tripartite and output-based GVC measures.

r-gsdesigntune 0.1.0
Propagated dependencies: r-rlang@1.1.6 r-r6@2.6.1 r-progressr@0.18.0 r-gsdesign@3.8.0 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://nanx.me/gsDesignTune/
Licenses: Expat
Build system: r
Synopsis: Dependency-Aware Scenario Exploration for Group Sequential Designs
Description:

This package provides systematic, dependency-aware exploration of group sequential designs created with gsDesign'. Supports reproducible grid and random search over user-defined candidate sets, parallel evaluation via the future framework, standardized metric extraction, and auditable reporting for design-space evaluation and trade-off analysis. Methods for group sequential design are described in Anderson (2025) <doi:10.32614/CRAN.package.gsDesign>. The future framework for parallel processing is described in Bengtsson (2021) <doi:10.32614/RJ-2021-048>.

r-geess 1.0.0
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=geess
Licenses: GPL 2+
Build system: r
Synopsis: Modified Generalized Estimating Equations for Small-Sample Data
Description:

Analyze small-sample clustered or longitudinal data using modified generalized estimating equations with bias-adjusted covariance estimator. The package provides any combination of three modified generalized estimating equations and 11 bias-adjusted covariance estimators.

r-grpstring 0.3.2
Propagated dependencies: r-rcpp@1.1.0 r-plyr@1.8.9 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GrpString
Licenses: GPL 2
Build system: r
Synopsis: Patterns and Statistical Differences Between Two Groups of Strings
Description:

This package provides methods include converting series of event names to strings, finding common patterns in a group of strings, discovering featured patterns when comparing two groups of strings as well as the number and starting position of each pattern in each string, obtaining transition matrix, computing transition entropy, statistically comparing the difference between two groups of strings, and clustering string groups. Event names can be any action names or labels such as events in log files or areas of interest (AOIs) in eye tracking research.

r-ggenemy 0.1.0
Propagated dependencies: r-ggplot2@4.0.1 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/andytai7/GGenemy
Licenses: Expat
Build system: r
Synopsis: Audit 'ggplot2' Visualizations for Accessibility and Best Practices
Description:

Audits ggplot2 visualizations for accessibility issues, misleading practices, and readability problems. Checks for color accessibility concerns including colorblind-unfriendly palettes, misleading scale manipulations such as truncated axes and dual y-axes, text readability issues like small fonts and overlapping labels, and general accessibility barriers. Provides comprehensive audit reports with actionable suggestions for improvement. Color vision deficiency simulation uses methods from the colorspace package Zeileis et al. (2020) <doi:10.18637/jss.v096.i01>. Contrast calculations follow WCAG 2.1 guidelines (W3C 2018 <https://www.w3.org/WAI/WCAG21/Understanding/contrast-minimum>).

r-ggallin 0.1.2
Propagated dependencies: r-scales@1.4.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/shabbychef/ggallin
Licenses: LGPL 3
Build system: r
Synopsis: Grab Bag of 'ggplot2' Functions
Description:

Extra geoms and scales for ggplot2', including geom_cloud(), a Normal density cloud replacement for errorbars; transforms ssqrt_trans and pseudolog10_trans, which are loglike but appropriate for negative data; interp_trans() and warp_trans() which provide scale transforms based on interpolation; and an infix compose operator for scale transforms.

r-gm 2.0.0
Propagated dependencies: r-htmltools@0.5.8.1 r-erify@0.6.0 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/flujoo/gm
Licenses: Expat
Build system: r
Synopsis: Create Music with Ease
Description:

This package provides a simple and intuitive high-level language for music representation. Generates and embeds music scores and audio files in RStudio', R Markdown documents, and R Jupyter Notebooks'. Internally, uses MusicXML <https://github.com/w3c/musicxml> to represent music, and MuseScore <https://musescore.org/> to convert MusicXML'.

r-gamlss-demo 4.3-3
Propagated dependencies: r-rpanel@1.1-5.2 r-gamlss-tr@5.1-9 r-gamlss-dist@6.1-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://www.gamlss.org/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Demos for GAMLSS
Description:

Demos for smoothing and gamlss.family distributions.

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