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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-graph4lg 1.8.0
Propagated dependencies: r-vegan@2.7-2 r-tidyr@1.3.1 r-stringr@1.6.0 r-spatstat-linnet@3.3-2 r-spatstat-geom@3.6-1 r-sp@2.2-0 r-sf@1.0-23 r-rdpack@2.6.4 r-raster@3.6-32 r-rappdirs@0.3.3 r-pegas@1.3 r-matrix@1.7-4 r-mass@7.3-65 r-igraph@2.2.1 r-hierfstat@0.5-11 r-ggplot2@4.0.1 r-gdistance@1.6.5 r-foreign@0.8-90 r-ecodist@2.1.3 r-adegenet@2.1.11
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=graph4lg
Licenses: GPL 2
Build system: r
Synopsis: Build Graphs for Landscape Genetics Analysis
Description:

Build graphs for landscape genetics analysis. This set of functions can be used to import and convert spatial and genetic data initially in different formats, import landscape graphs created with GRAPHAB software (Foltete et al., 2012) <doi:10.1016/j.envsoft.2012.07.002>, make diagnosis plots of isolation by distance relationships in order to choose how to build genetic graphs, create graphs with a large range of pruning methods, weight their links with several genetic distances, plot and analyse graphs, compare them with other graphs. It uses functions from other packages such as adegenet (Jombart, 2008) <doi:10.1093/bioinformatics/btn129> and igraph (Csardi et Nepusz, 2006) <https://igraph.org/>. It also implements methods commonly used in landscape genetics to create graphs, described by Dyer et Nason (2004) <doi:10.1111/j.1365-294X.2004.02177.x> and Greenbaum et Fefferman (2017) <doi:10.1111/mec.14059>, and to analyse distance data (van Strien et al., 2015) <doi:10.1038/hdy.2014.62>.

r-gamlss-tr 5.1-9
Propagated dependencies: r-gamlss-dist@6.1-1 r-gamlss@5.5-0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://www.gamlss.com/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Generating and Fitting Truncated `gamlss.family' Distributions
Description:

This is an add on package to GAMLSS. The purpose of this package is to allow users to defined truncated distributions in GAMLSS models. The main function gen.trun() generates truncated version of an existing GAMLSS family distribution.

r-garch-x 1.0
Propagated dependencies: r-pso@1.0.4 r-gensa@1.1.15 r-ga@3.2.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GARCH.X
Licenses: GPL 2+
Build system: r
Synopsis: Estimation and Exogenous Covariate Selection for GARCH-X Models
Description:

Estimates the parameters of a GARCH-X model with exogenous covariates, performs hypothesis tests for the parameters returning the p-values, and uses False Discovery Rate p-value corrections to select the exogenous variables.

r-ggpcp 0.2.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/heike/ggpcp
Licenses: GPL 3
Build system: r
Synopsis: Parallel Coordinate Plots in the 'ggplot2' Framework
Description:

Modern Parallel Coordinate Plots have been introduced in the 1980s as a way to visualize arbitrarily many numeric variables. This Grammar of Graphics implementation also incorporates categorical variables into the plots in a principled manner. By separating the data managing part from the visual rendering, we give full access to the users while keeping the number of parameters manageably low.

r-geomander 2.5.2
Propagated dependencies: r-tinytiger@0.0.11 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-sf@1.0-23 r-rlang@1.1.6 r-readr@2.1.6 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-geos@0.2.4 r-dplyr@1.1.4 r-dataverse@0.3.16 r-cli@3.6.5 r-censable@0.0.8 r-baf@0.0.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://christophertkenny.com/geomander/
Licenses: FSDG-compatible
Build system: r
Synopsis: Geographic Tools for Studying Gerrymandering
Description:

This package provides a compilation of tools to complete common tasks for studying gerrymandering. This focuses on the geographic tool side of common problems, such as linking different levels of spatial units or estimating how to break up units. Functions exist for creating redistricting-focused data for the US.

r-ggshadow 0.0.5
Propagated dependencies: r-vctrs@0.6.5 r-scales@1.4.0 r-rlang@1.1.6 r-glue@1.8.0 r-ggplot2@4.0.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/marcmenem/ggshadow/
Licenses: GPL 2
Build system: r
Synopsis: Shadow and Glow Geoms for 'ggplot2'
Description:

This package provides a collection of Geoms for R's ggplot2 library. geom_shadowpath(), geom_shadowline(), geom_shadowstep() and geom_shadowpoint() functions draw a shadow below lines to make busy plots more aesthetically pleasing. geom_glowpath(), geom_glowline(), geom_glowstep() and geom_glowpoint() add a neon glow around lines to get a steampunk style.

r-ggnormalviolin 0.2.1
Propagated dependencies: r-scales@1.4.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/wjschne/ggnormalviolin
Licenses: CC0
Build system: r
Synopsis: 'ggplot2' Extension to Make Normal Violin Plots
Description:

Uses ggplot2 to create normally distributed violin plots with specified means and standard deviations. This function can be useful in showing hypothetically normal distributions and confidence intervals.

r-glmulti 1.0.8
Dependencies: openjdk@25
Propagated dependencies: r-rjava@1.0-11 r-leaps@3.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=glmulti
Licenses: GPL 2+
Build system: r
Synopsis: Model Selection and Multimodel Inference Made Easy
Description:

Automated model selection and model-averaging. Provides a wrapper for glm and other functions, automatically generating all possible models (under constraints set by the user) with the specified response and explanatory variables, and finding the best models in terms of some Information Criterion (AIC, AICc or BIC). Can handle very large numbers of candidate models. Features a Genetic Algorithm to find the best models when an exhaustive screening of the candidates is not feasible.

r-gse 4.2-4
Propagated dependencies: r-rrcov@1.7-7 r-robustbase@0.99-6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mass@7.3-65 r-ggplot2@4.0.1 r-cellwise@2.5.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GSE
Licenses: GPL 2+
Build system: r
Synopsis: Robust Estimation in the Presence of Cellwise and Casewise Contamination and Missing Data
Description:

Robust Estimation of Multivariate Location and Scatter in the Presence of Cellwise and Casewise Contamination and Missing Data.

r-garcom 1.2.2
Propagated dependencies: r-vcfr@1.15.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GARCOM
Licenses: Expat
Build system: r
Synopsis: Gene and Region Counting of Mutations ("GARCOM")
Description:

Gene and Region Counting of Mutations (GARCOM) package computes mutation (or alleles) counts per gene per individuals based on gene annotation or genomic base pair boundaries. It comes with features to accept data formats in plink(.raw) and VCF. It provides users flexibility to extract and filter individuals, mutations and genes of interest.

r-git4r 0.1.2
Propagated dependencies: r-git2r@0.36.2 r-diffr@0.3.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/johnxhobbs/git4r
Licenses: Expat
Build system: r
Synopsis: Interactive Git for R
Description:

An interactive git user interface from the R command line. Intuitive tools to make commits, branches, remotes, and diffs an integrated part of R coding. Built on git2r, a system installation of git is not required and has default on-premises remote option.

r-gamboostlss 2.2-0
Propagated dependencies: r-stabs@0.6-4 r-mboost@2.9-11 r-gamlss-dist@6.1-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/boost-R/gamboostLSS
Licenses: GPL 2
Build system: r
Synopsis: Boosting Methods for 'GAMLSS'
Description:

Boosting models for fitting generalized additive models for location, shape and scale ('GAMLSS') to potentially high dimensional data.

r-genehummus 1.0.11
Propagated dependencies: r-stringr@1.6.0 r-rentrez@1.2.4 r-httr@1.4.7 r-dplyr@1.1.4 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/NCBI-Hackathons/GeneHummus
Licenses: Expat
Build system: r
Synopsis: Pipeline to Define Gene Families in Legumes and Beyond
Description:

This package provides a pipeline with high specificity and sensitivity in extracting proteins from the RefSeq database (National Center for Biotechnology Information). Manual identification of gene families is highly time-consuming and laborious, requiring an iterative process of manual and computational analysis to identify members of a given family. The pipelines implements an automatic approach for the identification of gene families based on the conserved domains that specifically define that family. See Die et al. (2018) <doi:10.1101/436659> for more information and examples.

r-gridgraphviz 0.3-2
Dependencies: graphviz@7.0.1
Propagated dependencies: r-rgraphviz@2.54.0 r-graph@1.88.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://r-forge.r-project.org/projects/gridgraph/
Licenses: GPL 2+
Build system: r
Synopsis: Drawing Graphs with 'grid'
Description:

This package provides functions for drawing node-and-edge graphs that have been laid out by graphviz'. This provides an alternative rendering to that provided by the Rgraphviz package, with two main advantages: the rendering provided by gridGraphviz should be more similar to what graphviz itself would draw; and rendering with grid allows for post-hoc customisations using the named viewports and grobs that gridGraphviz produces.

r-gmcplite 0.1.6
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://merck.github.io/gMCPLite/
Licenses: GPL 3
Build system: r
Synopsis: Lightweight Graph Based Multiple Comparison Procedures
Description:

This package provides a lightweight fork of gMCP with functions for graphical described multiple test procedures introduced in Bretz et al. (2009) <doi:10.1002/sim.3495> and Bretz et al. (2011) <doi:10.1002/bimj.201000239>. Implements a flexible function using ggplot2 to create multiplicity graph visualizations. Contains instructions of multiplicity graph and graphical testing for group sequential design, described in Maurer and Bretz (2013) <doi:10.1080/19466315.2013.807748>, with necessary unit testing using testthat'.

r-graphframes 0.1.2
Propagated dependencies: r-tibble@3.3.0 r-sparklyr@1.9.3 r-forge@0.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/rstudio/graphframes
Licenses: ASL 2.0 FSDG-compatible
Build system: r
Synopsis: Interface for 'GraphFrames'
Description:

This package provides a sparklyr <https://spark.rstudio.com/> extension that provides an R interface for GraphFrames <https://graphframes.github.io/>. GraphFrames is a package for Apache Spark that provides a DataFrame-based API for working with graphs. Functionality includes motif finding and common graph algorithms, such as PageRank and Breadth-first search.

r-gbutils 0.5.1
Propagated dependencies: r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://geobosh.github.io/gbutils/
Licenses: GPL 2+
Build system: r
Synopsis: Utilities for Simulation, Plots, Quantile Functions and Programming
Description:

Plot density and distribution functions with automatic selection of suitable regions. Numerically invert (compute quantiles) distribution functions. Simulate real and complex numbers from distributions of their magnitude and arguments. Optionally, the magnitudes and/or arguments may be fixed in almost arbitrary ways. Create polynomials from roots given in Cartesian or polar form. Small programming utilities: check if an object is identical to NA, count positional arguments in a call, set intersection of more than two sets, check if an argument is unnamed, compute the graph of S4 classes in packages.

r-generalhoslem 1.3.4
Propagated dependencies: r-reshape@0.8.10 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=generalhoslem
Licenses: GPL 2
Build system: r
Synopsis: Goodness of Fit Tests for Logistic Regression Models
Description:

This package provides functions to assess the goodness of fit of binary, multinomial and ordinal logistic models. Included are the Hosmer-Lemeshow tests (binary, multinomial and ordinal) and the Lipsitz and Pulkstenis-Robinson tests (ordinal).

r-gnorm 1.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://github.com/maryclare/gnorm
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Normal/Exponential Power Distribution
Description:

This package provides functions for obtaining generalized normal/exponential power distribution probabilities, quantiles, densities and random deviates. The generalized normal/exponential power distribution was introduced by Subbotin (1923) and rediscovered by Nadarajah (2005). The parametrization given by Nadarajah (2005) <doi:10.1080/02664760500079464> is used.

r-gpemr 0.1.0
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GPEMR
Licenses: Expat
Build system: r
Synopsis: Growth Parameter Estimation Method
Description:

This package provides functions for simulating and estimating parameters of various growth models, including Logistic, Exponential, Theta-logistic, Von-Bertalanffy, and Gompertz models. The package supports both simulated and real data analysis, including parameter estimation, visualization, and calculation of global and local estimates. The methods are based on research described by Md Aktar Ul Karim and Amiya Ranjan Bhowmick (2022) in (<https://www.researchsquare.com/article/rs-2363586/v1>). An interactive web application is also available at [GPEMR Web App](<https://gpem-r.shinyapps.io/GPEM-R/>).

r-gremlins 0.2.1
Propagated dependencies: r-r6@2.6.1 r-pbmcapply@1.5.1 r-igraph@2.2.1 r-blockmodels@1.1.5 r-aricode@1.0.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://GrossSBM.github.io/GREMLINS/
Licenses: GPL 3
Build system: r
Synopsis: Generalized Multipartite Networks
Description:

We define generalized multipartite networks as the joint observation of several networks implying some common pre-specified groups of individuals. The aim is to fit an adapted version of the popular stochastic block model to multipartite networks, as described in Bar-hen, Barbillon and Donnet (2020) <arXiv:1807.10138>.

r-gamair 1.0-2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gamair
Licenses: GPL 2+
Build system: r
Synopsis: Data for 'GAMs: An Introduction with R'
Description:

Data sets and scripts used in the book Generalized Additive Models: An Introduction with R', Wood (2006,2017) CRC.

r-globaltrends 0.0.14
Propagated dependencies: r-zoo@1.8-14 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rsqlite@2.4.4 r-rlang@1.1.6 r-purrr@1.2.0 r-lubridate@1.9.4 r-gtrendsr@1.5.2 r-ggplot2@4.0.1 r-forecast@8.24.0 r-forcats@1.0.1 r-dplyr@1.1.4 r-dbplyr@2.5.1 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/ha-pu/globaltrends/
Licenses: Expat
Build system: r
Synopsis: Download and Measure Global Trends Through Google Search Volumes
Description:

Google offers public access to global search volumes from its search engine through the Google Trends portal. The package downloads these search volumes provided by Google Trends and uses them to measure and analyze the distribution of search scores across countries or within countries. The package allows researchers and analysts to use these search scores to investigate global trends based on patterns within these scores. This offers insights such as degree of internationalization of firms and organizations or dissemination of political, social, or technological trends across the globe or within single countries. An outline of the package's methodological foundations and potential applications is available as a working paper: <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3969013>.

r-gnfit 0.2.0
Propagated dependencies: r-rmutil@1.1.10 r-ismev@1.43
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gnFit
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Goodness of Fit Test for Continuous Distribution Functions
Description:

Computes the test statistic and p-value of the Cramer-von Mises and Anderson-Darling test for some continuous distribution functions proposed by Chen and Balakrishnan (1995) <http://asq.org/qic/display-item/index.html?item=11407>. In addition to our classic distribution functions here, we calculate the Goodness of Fit (GoF) test to dataset which follows the extreme value distribution function, without remembering the formula of distribution/density functions. Calculates the Value at Risk (VaR) and Average VaR are another important risk factors which are estimated by using well-known distribution functions. Pflug and Romisch (2007, ISBN: 9812707409) is a good reference to study the properties of risk measures.

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