_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-grizbayr 1.3.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/rangi513/grizbayr
Licenses: Expat
Build system: r
Synopsis: Bayesian Inference for A|B and Bandit Marketing Tests
Description:

Uses simple Bayesian conjugate prior update rules to calculate the win probability of each option, value remaining in the test, and percent lift over the baseline for various marketing objectives. References: Fink, Daniel (1997) "A Compendium of Conjugate Priors" <https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>. Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <https://vwo.com/downloads/VWO_SmartStats_technical_whitepaper.pdf>.

r-goalp 0.3.1
Propagated dependencies: r-lpsolve@5.6.23
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=goalp
Licenses: GPL 3+
Build system: r
Synopsis: Weighted and Lexicographic Goal Programming Interface
Description:

Solves goal programming problems of the weighted and lexicographic type, as well as combinations of the two, as described by Ignizio (1983) <doi:10.1016/0305-0548(83)90003-5>. Allows for a simple human-readable input describing the problem as a series of equations. Relies on the lpSolve package to solve the underlying linear optimisation problem.

r-getmstatistic 0.2.2
Propagated dependencies: r-stargazer@5.2.3 r-psych@2.5.6 r-metafor@4.8-0 r-gtable@0.3.6 r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://magosil86.github.io/getmstatistic/
Licenses: Expat
Build system: r
Synopsis: Quantifying Systematic Heterogeneity in Meta-Analysis
Description:

Quantifying systematic heterogeneity in meta-analysis using R. The M statistic aggregates heterogeneity information across multiple variants to, identify systematic heterogeneity patterns and their direction of effect in meta-analysis. It's primary use is to identify outlier studies, which either show "null" effects or consistently show stronger or weaker genetic effects than average across, the panel of variants examined in a GWAS meta-analysis. In contrast to conventional heterogeneity metrics (Q-statistic, I-squared and tau-squared) which measure random heterogeneity at individual variants, M measures systematic (non-random) heterogeneity across multiple independently associated variants. Systematic heterogeneity can arise in a meta-analysis due to differences in the study characteristics of participating studies. Some of the differences may include: ancestry, allele frequencies, phenotype definition, age-of-disease onset, family-history, gender, linkage disequilibrium and quality control thresholds. See <https://magosil86.github.io/getmstatistic/> for statistical statistical theory, documentation and examples.

r-googlenlp 0.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/BrianWeinstein/googlenlp
Licenses: Expat
Build system: r
Synopsis: An Interface to Google's Cloud Natural Language API
Description:

Interact with Google's Cloud Natural Language API <https://cloud.google.com/natural-language/> (v1) via R. The API has four main features, all of which are available through this R package: syntax analysis and part-of-speech tagging, entity analysis, sentiment analysis, and language identification.

r-grcdata 1.0
Propagated dependencies: r-nloptr@2.2.1 r-cubature@2.1.4-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GRCdata
Licenses: GPL 3+
Build system: r
Synopsis: Parameter Inference and Optimal Designs for Grouped and/or Right-Censored Count Data
Description:

We implement two main functions. The first function uses a given grouped and/or right-censored grouping scheme and empirical data to infer parameters, and implements chi-square goodness-of-fit tests. The second function searches for the global optimal grouping scheme of grouped and/or right-censored count responses in surveys.

r-gsw 1.2-0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://teos-10.github.io/GSW-R/
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Gibbs Sea Water Functions
Description:

This package provides an interface to the Gibbs SeaWater ('TEOS-10') C library, version 3.06-16-0 (commit 657216dd4f5ea079b5f0e021a4163e2d26893371', dated 2022-10-11, available at <https://github.com/TEOS-10/GSW-C>, which stems from Matlab and other code written by members of Working Group 127 of SCOR'/'IAPSO (Scientific Committee on Oceanic Research / International Association for the Physical Sciences of the Oceans).

r-gselection 0.1.0
Propagated dependencies: r-sam@1.2 r-penalized@0.9-53 r-gdata@3.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GSelection
Licenses: GPL 3
Build system: r
Synopsis: Genomic Selection
Description:

Genomic selection is a specialized form of marker assisted selection. The package contains functions to select important genetic markers and predict phenotype on the basis of fitted training data using integrated model framework (Guha Majumdar et. al. (2019) <doi:10.1089/cmb.2019.0223>) developed by combining one additive (sparse additive models by Ravikumar et. al. (2009) <doi:10.1111/j.1467-9868.2009.00718.x>) and one non-additive (hsic lasso by Yamada et. al. (2014) <doi:10.1162/NECO_a_00537>) model.

r-gmvarkit 2.2.1
Propagated dependencies: r-pbapply@1.7-4 r-mvnfast@0.2.8 r-gsl@2.1-9 r-brobdingnag@1.2-9
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gmvarkit
Licenses: GPL 3
Build system: r
Synopsis: Estimate Gaussian and Student's t Mixture Vector Autoregressive Models
Description:

Unconstrained and constrained maximum likelihood estimation of structural and reduced form Gaussian mixture vector autoregressive, Student's t mixture vector autoregressive, and Gaussian and Student's t mixture vector autoregressive models, quantile residual tests, graphical diagnostics, simulations, forecasting, and estimation of generalized impulse response function and generalized forecast error variance decomposition. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>, Savi Virolainen (2025) <doi:10.1080/07350015.2024.2322090>, Savi Virolainen (in press) <doi:10.1016/j.ecosta.2025.09.003>.

r-genemodel 1.1.0
Propagated dependencies: r-stringr@1.6.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/greymonroe/genemodel
Licenses: GPL 2
Build system: r
Synopsis: Gene Model Plotting in R
Description:

Using simple input, this package creates plots of gene models. Users can create plots of alternatively spliced gene variants and the positions of mutations and other gene features.

r-ggdemetra 0.2.9
Dependencies: openjdk@25
Propagated dependencies: r-rjdemetra@0.2.8 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://aqlt.github.io/ggdemetra/
Licenses: FSDG-compatible
Build system: r
Synopsis: 'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra'
Description:

This package provides ggplot2 functions to return the results of seasonal and trading day adjustment made by RJDemetra'. RJDemetra is an R interface around JDemetra+ (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks.

r-ggseqplot 0.8.9
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://maraab23.github.io/ggseqplot/
Licenses: GPL 3+
Build system: r
Synopsis: Render Sequence Plots using 'ggplot2'
Description:

This package provides a set of wrapper functions that mainly re-produces most of the sequence plots rendered with TraMineR::seqplot(). Whereas TraMineR uses base R to produce the plots this library draws on ggplot2'. The plots are produced on the basis of a sequence object defined with TraMineR::seqdef(). The package automates the reshaping and plotting of sequence data. Resulting plots are of class ggplot', i.e. components can be added and tweaked using + and regular ggplot2 functions.

r-gridgeometry 0.4-0
Propagated dependencies: r-polyclip@1.10-7
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/pmur002/gridgeometry
Licenses: GPL 2+
Build system: r
Synopsis: Polygon Geometry in 'grid'
Description:

This package provides functions for performing polygon geometry with grid grobs. This allows complex shapes to be defined by combining simpler shapes.

r-glcmtextures 0.6.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://ailich.github.io/GLCMTextures/
Licenses: GPL 3+
Build system: r
Synopsis: GLCM Textures of Raster Layers
Description:

Calculates grey level co-occurrence matrix (GLCM) based texture measures (Hall-Beyer (2017) <https://prism.ucalgary.ca/bitstream/handle/1880/51900/texture%20tutorial%20v%203_0%20180206.pdf>; Haralick et al. (1973) <doi:10.1109/TSMC.1973.4309314>) of raster layers using a sliding rectangular window. It also includes functions to quantize a raster into grey levels as well as tabulate a glcm and calculate glcm texture metrics for a matrix.

r-gsbm 0.2.2
Propagated dependencies: r-softimpute@1.4-3 r-rspectra@0.16-2 r-matrix@1.7-4 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=gsbm
Licenses: GPL 3
Build system: r
Synopsis: Estimate Parameters in the Generalized SBM
Description:

Given an adjacency matrix drawn from a Generalized Stochastic Block Model with missing observations, this package robustly estimates the probabilities of connection between nodes and detects outliers nodes, as describes in Gaucher, Klopp and Robin (2019) <arXiv:1911.13122>.

r-greensd 0.1.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/billbillbilly/greenSD
Licenses: GPL 3
Build system: r
Synopsis: Access and Analyze Global GreenSpace Spatial Data
Description:

Access and analyze multi-band greenspace seasonality data cubes (available for 1,028 major global cities), global Normalized Difference Vegetation Index / land cover data from the European Space Agency WorldCover 10m Dataset, and Sentinel-2-l2a images. Users can download data using bounding boxes, city names, and filter by year or seasonal time window. The package also supports calculating human exposure to greenspace using a population-weighted greenspace exposure model introduced by Chen et al. (2022) <doi:10.1038/s41467-022-32258-4> based on Global Human Settlement Layer population data, and calculating a set of greenspace morphology metrics at patch and landscape levels.

r-giant 1.3.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GiANT
Licenses: Artistic License 2.0
Build system: r
Synopsis: Gene Set Uncertainty in Enrichment Analysis
Description:

Toolbox for various enrichment analysis methods and quantification of uncertainty of gene sets, Schmid et al. (2016) <doi:10.1093/bioinformatics/btw030>.

r-ggparty 1.0.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/martin-borkovec/ggparty
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: 'ggplot' Visualizations for the 'partykit' Package
Description:

Extends ggplot2 functionality to the partykit package. ggparty provides the necessary tools to create clearly structured and highly customizable visualizations for tree-objects of the class party'.

r-geemediate 1.1.4
Propagated dependencies: r-gee@4.13-29
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GEEmediate
Licenses: GPL 3+
Build system: r
Synopsis: Mediation Analysis for Generalized Linear Models Using the Difference Method
Description:

Causal mediation analysis for a single exposure/treatment and a single mediator, both allowed to be either continuous or binary. The package implements the difference method and provides point and interval estimates as well as testing for the natural direct and indirect effects and the mediation proportion. Nevo, Xiao and Spiegelman (2017) <doi:10.1515/ijb-2017-0006>.

r-geommc 1.3.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/vroys/geommc
Licenses: GPL 3+
Build system: r
Synopsis: Geometric Markov Chain Sampling
Description:

Simulates from discrete and continuous target distributions using geometric Metropolis-Hastings (MH) algorithms. Users specify the target distribution by an R function that evaluates the log un-normalized pdf or pmf. The package also contains a function implementing a specific geometric MH algorithm for performing high-dimensional Bayesian variable selection.

r-gtbasedim 1.0.0
Propagated dependencies: r-rweka@0.4-47 r-coopgame@0.2.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GTbasedIM
Licenses: GPL 2
Build system: r
Synopsis: Game Theory-Based Influence Measures
Description:

Understanding how features influence a specific response variable becomes crucial in classification problems, with applications ranging from medical diagnosis to customer behavior analysis. This packages provides tools to compute such an influence measure grounded on game theory concepts. In particular, the influence measures presented in Davila-Pena, Saavedra-Nieves, and Casas-Méndez (2024) <doi:10.48550/arXiv.2408.02481> can be obtained.

r-gofshiny 0.1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GOFShiny
Licenses: GPL 2
Build system: r
Synopsis: Interactive Document for Working with Goodness of Fit Analysis
Description:

An interactive document on the topic of goodness of fit analysis using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://predanalyticssessions1.shinyapps.io/ChiSquareGOF/>.

r-gendata 1.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gendata
Licenses: GPL 3
Build system: r
Synopsis: Generate and Modify Synthetic Datasets
Description:

Set of functions to create datasets using a correlation matrix.

r-gt 1.3.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://gt.rstudio.com
Licenses: Expat
Build system: r
Synopsis: Easily Create Presentation-Ready Display Tables
Description:

Build display tables from tabular data with an easy-to-use set of functions. With its progressive approach, we can construct display tables with a cohesive set of table parts. Table values can be formatted using any of the included formatting functions. Footnotes and cell styles can be precisely added through a location targeting system. The way in which gt handles things for you means that you don't often have to worry about the fine details.

r-gtests 0.2
Propagated dependencies: r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gTests
Licenses: GPL 2+
Build system: r
Synopsis: Graph-Based Two-Sample Tests
Description:

Four graph-based tests are provided for testing whether two samples are from the same distribution. It works for both continuous data and discrete data.

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Total results: 69112