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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 search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-geomapdata 2.0-2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=geomapdata
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Data for Topographic and Geologic Mapping
Description:

Data sets included here are for use with package GEOmap. These include world map, USA map, Coso map, Japan Map.

r-glscalibrator 0.1.0
Propagated dependencies: r-stringr@1.6.0 r-maps@3.4.3 r-magrittr@2.0.5 r-lubridate@1.9.5 r-dplyr@1.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/fabbiologia/glscalibrator
Licenses: Expat
Build system: r
Synopsis: Automated Calibration and Analysis of 'GLS' (Global Location Sensor) Data
Description:

This package provides a fully automated workflow for calibrating and analyzing light-level geolocation ('GLS') data from seabirds and other wildlife. The glscalibrator package auto-discovers birds from directory structures, automatically detects calibration periods from the first days of deployment, processes multiple individuals in batch mode, and generates standardized outputs including position estimates, diagnostic plots, and quality control metrics. Implements the established threshold workflow internally, following the methods described in SGAT (Wotherspoon et al. (2016) <https://github.com/SWotherspoon/SGAT>), GeoLight (Lisovski et al. (2012) <doi:10.1111/j.2041-210X.2012.00185.x>), and TwGeos (Lisovski et al. (2019) <https://github.com/slisovski/TwGeos>).

r-gandatamodel 2.0.1
Propagated dependencies: r-tensorflow@2.20.0 r-rcpp@1.1.1-1.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=ganDataModel
Licenses: GPL 2+
Build system: r
Synopsis: Build a Metric Subspaces Data Model for a Data Source
Description:

Neural networks are applied to create a density value function which approximates density values for a data source. The trained neural network is analyzed for different levels. For each level metric subspaces with density values above a level are determined. The obtained set of metric subspaces and the trained neural network are assembled into a data model. A prerequisite is the definition of a data source, the generation of generative data and the calculation of density values. These tasks are executed using package ganGenerativeData <https://cran.r-project.org/package=ganGenerativeData>.

r-gggap 1.0.1
Propagated dependencies: r-ggplot2@4.0.3 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/cmoralesmx/gggap
Licenses: GPL 3
Build system: r
Synopsis: Streamlined Creation of Segments on the Y-Axis of 'ggplot2' Plots
Description:

The function gggap() streamlines the creation of segments on the y-axis of ggplot2 plots which is otherwise not a trivial task to accomplish.

r-geex 1.1.1
Propagated dependencies: r-rootsolve@1.8.2.4 r-numderiv@2016.8-1.1 r-matrix@1.7-5 r-lme4@2.0-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/bsaul/geex
Licenses: Expat
Build system: r
Synopsis: An API for M-Estimation
Description:

This package provides a general, flexible framework for estimating parameters and empirical sandwich variance estimator from a set of unbiased estimating equations (i.e., M-estimation in the vein of Stefanski & Boos (2002) <doi:10.1198/000313002753631330>). All examples from Stefanski & Boos (2002) are published in the corresponding Journal of Statistical Software paper "The Calculus of M-Estimation in R with geex" by Saul & Hudgens (2020) <doi:10.18637/jss.v092.i02>. Also provides an API to compute finite-sample variance corrections.

r-glmbasedraschestimation 0.2.0
Propagated dependencies: r-shiny@1.13.0 r-readxl@1.5.0 r-haven@2.5.5 r-dt@0.34.0 r-bslib@0.11.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/DrAhmedSamir/GLMBasedRaschEstimation
Licenses: Expat
Build system: r
Synopsis: GLM-Based Estimation for Rasch Model Parameters
Description:

This package provides functions for estimating Rasch model parameters using the Generalized Linear Model (GLM) framework. The methods implemented are based on Brown (2018, ISBN:978-3-319-93547-8) <doi:10.1007/978-3-319-93549-2> and Debelak et al. (2022, ISBN:978-1-138-71046-7) <doi:10.1201/9781315200620>.

r-gawdis 0.1.5
Propagated dependencies: r-ga@3.2.5 r-fd@1.0-12.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/pavel-fibich/gawdis/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Multi-Trait Dissimilarity with more Uniform Contributions
Description:

R function gawdis() produces multi-trait dissimilarity with more uniform contributions of different traits. de Bello et al. (2021) <doi:10.1111/2041-210X.13537> presented the approach based on minimizing the differences in the correlation between the dissimilarity of each trait, or groups of traits, and the multi-trait dissimilarity. This is done using either an analytic or a numerical solution, both available in the function.

r-geslar 1.0-1
Propagated dependencies: r-dplyr@1.2.1 r-cli@3.6.6 r-arrow@24.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/EireExtremes/geslaR
Licenses: GPL 3+
Build system: r
Synopsis: Get and Manipulate the GESLA Dataset
Description:

Promote access to the GESLA <https://gesla787883612.wordpress.com> (Global Extreme Sea Level Analysis) dataset, a higher-frequency sea-level record data from all over the world. It provides functions to download it entirely, or query subsets directly into R, without the need of downloading the full dataset. Also, it provides a built-in web-application, so that users can apply basic filters to select the data of interest, generating informative plots, and showing the selected sites.

r-genset 0.1.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=genset
Licenses: GPL 2
Build system: r
Synopsis: Generates Multiple Data Sets
Description:

Generate multiple data sets for educational purposes to demonstrate the importance of multiple regression. The genset function generates a data set from an initial data set to have the same summary statistics (mean, median, and standard deviation) but opposing regression results.

r-gge 1.10
Propagated dependencies: r-reshape2@1.4.5 r-nipals@1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://kwstat.github.io/gge/
Licenses: Expat
Build system: r
Synopsis: Genotype Plus Genotype-by-Environment Biplots
Description:

Create biplots for GGE (genotype plus genotype-by-environment) and GGB (genotype plus genotype-by-block-of-environments) models. See Laffont et al. (2013) <doi:10.2135/cropsci2013.03.0178>.

r-gipsda 0.1.2
Propagated dependencies: r-tidyr@1.3.2 r-tibble@3.3.1 r-stringi@1.8.7 r-rlang@1.2.0 r-permutations@1.1-6 r-patchwork@1.3.2 r-numbers@0.9-2 r-mass@7.3-65 r-lattice@0.22-9 r-jsonlite@2.0.0 r-gips@1.2.3 r-ggplot2@4.0.3 r-dplyr@1.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://AntoniKingston.github.io/gipsDA/
Licenses: GPL 3
Build system: r
Synopsis: Training DA Models Utilizing 'gips'
Description:

Extends classical linear and quadratic discriminant analysis by incorporating permutation group symmetries into covariance matrix estimation. The package leverages methodology from the gips framework to identify and impose permutation structures that act as a form of regularization, improving stability and interpretability in settings with symmetric or exchangeable features. Several discriminant analysis variants are provided, including pooled and class-specific covariance models, as well as multi-class extensions with shared or independent symmetry structures. For more details about gips methodology see and Graczyk et al. (2022) <doi:10.1214/22-AOS2174> and Chojecki, Morgen, KoÅ odziejek (2025, <doi:10.18637/jss.v112.i07>).

r-gkwdist 1.1.4
Propagated dependencies: r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1 r-numderiv@2016.8-1.1 r-magrittr@2.0.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/evandeilton/gkwdist
Licenses: Expat
Build system: r
Synopsis: Generalized Kumaraswamy Distribution Family
Description:

This package implements the five-parameter Generalized Kumaraswamy ('gkw') distribution proposed by Carrasco, Ferrari and Cordeiro (2010) <doi:10.48550/arXiv.1004.0911> and its seven nested sub-families for modeling bounded continuous data on the unit interval (0,1). The gkw distribution extends the Kumaraswamy distribution described by Jones (2009) <doi:10.1016/j.stamet.2008.04.001>. Provides density, distribution, quantile, and random generation functions, along with analytical log-likelihood, gradient, and Hessian functions implemented in C++ via RcppArmadillo for maximum computational efficiency. Suitable for modeling proportions, rates, percentages, and indices exhibiting complex features such as asymmetry, or heavy tails and other shapes not adequately captured by standard distributions like simple Beta or Kumaraswamy.

r-gnomonicm 1.0.1
Propagated dependencies: r-triangle@1.1.0 r-minqa@1.2.8 r-kableextra@1.4.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gnomonicM
Licenses: GPL 2
Build system: r
Synopsis: Estimate Natural Mortality for Different Life Stages
Description:

Estimate natural mortality (M) throughout the life history for organisms, mainly fish and invertebrates, based on gnomonic interval approach proposed by Caddy (1996) <doi:10.1051/alr:1996023> and Martinez-Aguilar et al. (2005) <doi:10.1016/j.fishres.2004.04.008>. It includes estimation of duration of each gnomonic interval (life stage), the constant probability of death (G), and some basic plots.

r-gfdrmst 0.1.1
Propagated dependencies: r-tippy@0.1.0 r-shinywidgets@0.9.1 r-shinythemes@1.2.0 r-shinymatrix@0.8.1 r-shinyjs@2.1.1 r-shiny@1.13.0 r-plyr@1.8.9 r-mvtnorm@1.3-7 r-mass@7.3-65 r-lpsolve@5.6.23 r-gfdmcv@0.1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GFDrmst
Licenses: GPL 3+
Build system: r
Synopsis: Multiple RMST-Based Tests in General Factorial Designs
Description:

We implemented multiple tests based on the restricted mean survival time (RMST) for general factorial designs as described in Munko et al. (2024) <doi:10.1002/sim.10017>. Therefore, an asymptotic test, a groupwise bootstrap test, and a permutation test are incorporated with a Wald-type test statistic. The asymptotic and groupwise bootstrap test take the asymptotic exact dependence structure of the test statistics into account to gain more power. Furthermore, confidence intervals for RMST contrasts can be calculated and plotted and a stepwise extension that can improve the power of the multiple tests is available.

r-graph3d 0.2.0
Propagated dependencies: r-lazyeval@0.2.3 r-htmlwidgets@1.6.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/stla/graph3d
Licenses: GPL 3
Build system: r
Synopsis: Wrapper of the JavaScript Library 'vis-graph3d'
Description:

Create interactive visualization charts to draw data in three dimensional graphs. The graphs can be included in Shiny apps and R markdown documents, or viewed from the R console and RStudio Viewer. Based on the vis.js Graph3d module and the htmlwidgets R package.

r-ggfx 1.0.3
Propagated dependencies: r-rlang@1.2.0 r-ragg@1.5.2 r-magick@2.9.1 r-gtable@0.3.6 r-ggplot2@4.0.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://ggfx.data-imaginist.com
Licenses: Expat
Build system: r
Synopsis: Pixel Filters for 'ggplot2' and 'grid'
Description:

This package provides a range of filters that can be applied to layers from the ggplot2 package and its extensions, along with other graphic elements such as guides and theme elements. The filters are applied at render time and thus uses the exact pixel dimensions needed.

r-gace 1.0.0
Propagated dependencies: r-ggplot2@4.0.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/vinoalles/GACE
Licenses: Expat
Build system: r
Synopsis: Generalized Adaptive Capped Estimator for Time Series Forecasting
Description:

This package provides deterministic forecasting for weekly, monthly, quarterly, and yearly time series using the Generalized Adaptive Capped Estimator. The method includes preprocessing for missing and extreme values, extraction of multiple growth components (including long-term, short-term, rolling, and drift-based signals), volatility-aware asymmetric capping, optional seasonal adjustment via damped and normalized seasonal factors, and a recursive forecast formulation with moderated growth. The package includes a user-facing forecasting interface and a plotting helper for visualization. Related forecasting background is discussed in Hyndman and Athanasopoulos (2021) <https://otexts.com/fpp3/> and Hyndman and Khandakar (2008) <doi:10.18637/jss.v027.i03>. The method extends classical extrapolative forecasting approaches and is suited for operational and business planning contexts where stability and interpretability are important.

r-guess 0.3.0
Propagated dependencies: r-rsolnp@2.0.1 r-checkmate@2.3.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/finite-sample/guess
Licenses: Expat
Build system: r
Synopsis: Adjust Estimates of Learning for Guessing
Description:

This package provides tools to adjust estimates of learning for guessing-related bias in educational and survey research. Implements standard guessing correction methods and a sophisticated latent class model that leverages informative pre-post test transitions to account for guessing behavior. The package helps researchers obtain more accurate estimates of actual learning when respondents may guess on closed-ended knowledge items. For theoretical background and empirical validation, see Cor and Sood (2018) <https://gsood.com/research/papers/guess.pdf>.

r-geostan 0.8.2
Propagated dependencies: r-truncnorm@1.0-9 r-stanheaders@2.32.10 r-spdep@1.4-2 r-spdata@2.3.5 r-signs@0.1.2 r-sf@1.1-1 r-rstantools@2.6.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-2 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.1-1.1 r-matrix@1.7-5 r-mass@7.3-65 r-gridextra@2.3 r-ggplot2@4.0.3 r-bh@1.90.0-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://connordonegan.github.io/geostan/
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Spatial Analysis
Description:

For spatial data analysis; provides exploratory spatial analysis tools, spatial regression, spatial econometric, and disease mapping models, model diagnostics, and special methods for inference with small area survey data (e.g., the America Community Survey (ACS)) and censored population health monitoring data. Models are pre-specified using the Stan programming language, a platform for Bayesian inference using Markov chain Monte Carlo (MCMC). References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Donegan (2021) <doi:10.31219/osf.io/3ey65>; Donegan (2022) <doi:10.21105/joss.04716>; Donegan, Chun and Hughes (2020) <doi:10.1016/j.spasta.2020.100450>; Donegan, Chun and Griffith (2021) <doi:10.3390/ijerph18136856>; Morris et al. (2019) <doi:10.1016/j.sste.2019.100301>.

r-geelite 1.0.6
Propagated dependencies: r-tidyr@1.3.2 r-stringr@1.6.0 r-sf@1.1-1 r-rstudioapi@0.18.0 r-rsqlite@3.52.0 r-rnaturalearthdata@1.0.0 r-rnaturalearth@1.2.0 r-rgee@1.1.8 r-reticulate@1.46.0 r-reshape2@1.4.5 r-purrr@1.2.2 r-progress@1.2.3 r-magrittr@2.0.5 r-lubridate@1.9.5 r-knitr@1.51 r-jsonlite@2.0.0 r-h3jsr@1.3.1 r-googledrive@2.1.2 r-geojsonio@0.11.3 r-dplyr@1.2.1 r-data-table@1.18.4 r-crayon@1.5.3 r-cli@3.6.6
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=geeLite
Licenses: FSDG-compatible
Build system: r
Synopsis: Building and Managing Local Databases from 'Google Earth Engine'
Description:

Simplifies the creation, management, and updating of local databases using data extracted from Google Earth Engine ('GEE'). It integrates with GEE to store, aggregate, and process spatio-temporal data, leveraging SQLite for efficient, serverless storage. The geeLite package provides utilities for data transformation and supports real-time monitoring and analysis of geospatial features, making it suitable for researchers and practitioners in geospatial science. For details, see Kurbucz and Andrée (2025) "Building and Managing Local Databases from Google Earth Engine with the geeLite R Package" <https://hdl.handle.net/10986/43165>.

r-ggexametrika 1.1.1
Propagated dependencies: r-tidyr@1.3.2 r-igraph@2.3.1 r-gridextra@2.3 r-ggrepel@0.9.8 r-ggraph@2.2.2 r-ggplot2@4.0.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://kosugitti.github.io/ggExametrika/
Licenses: Expat
Build system: r
Synopsis: Visualization of 'exametrika' Output Using 'ggplot2'
Description:

This package provides ggplot2'-based visualization functions for output objects from the exametrika package, which implements test data engineering methods described in Shojima (2022, ISBN:978-981-16-9547-1). Supports a wide range of psychometric models including Item Response Theory, Latent Class Analysis, Latent Rank Analysis, Biclustering (binary, ordinal, and nominal), Bayesian Network Models, and related network models. All plot functions return ggplot2 objects that can be further customized by the user.

r-getlattes 1.0.0
Propagated dependencies: r-xml2@1.5.2 r-tibble@3.3.1 r-purrr@1.2.2 r-janitor@2.2.1 r-dplyr@1.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/roneyfraga/getLattes
Licenses: GPL 3
Build system: r
Synopsis: Import and Process Data from the 'Lattes' Curriculum Platform
Description:

Tool for import and process data from Lattes curriculum platform (<http://lattes.cnpq.br/>). The Brazilian government keeps an extensive base of curricula for academics from all over the country, with over 5 million registrations. The academic life of the Brazilian researcher, or related to Brazilian universities, is documented in Lattes'. Some information that can be obtained: professional formation, research area, publications, academics advisories, projects, etc. getLattes package allows work with Lattes data exported to XML format.

r-ggskewboxplots 1.0.0
Propagated dependencies: r-tidyr@1.3.2 r-rlang@1.2.0 r-ggplot2@4.0.3 r-dplyr@1.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=ggskewboxplots
Licenses: GPL 3+
Build system: r
Synopsis: Skew Boxplot Geoms for 'ggplot2'
Description:

This package provides ggplot2 extensions for creating skewed boxplots using several statistical methods (Kimber, 1990 <doi:10.2307/2347808>; Hubert and Vandervieren, 2008 <doi:10.1016/j.csda.2007.11.008>; Adil et al., 2015 <doi:10.18187/pjsor.v11i1.500>; Babura et al., 2017 <doi:10.1063/1.4982872>; Walker et al., 2018 <doi:10.1080/00031305.2018.1448891>). The package implements custom statistical transformations and geometries to visualize data distributions with an emphasis on skewness.

r-gsloid 0.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/benmarwick/gsloid
Licenses: Expat
Build system: r
Synopsis: Global Sea Level and Oxygen Isotope Data
Description:

This package contains published data sets for global benthic d18O data for 0-5.3 Myr <doi:10.1029/2004PA001071> and global sea levels based on marine sediment core data for 0-800 ka <doi:10.5194/cp-12-1-2016>.

Total packages: 72484