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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-genord 2.0.0
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 r-cubature@2.1.4-1 r-bbmle@1.0.25.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GenOrd
Licenses: GPL 3
Build system: r
Synopsis: Simulation of Discrete Random Variables with Given Correlation Matrix and Marginal Distributions via a Gaussian or Student's t Copula
Description:

This package provides a Gaussian or Student's t copula-based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.

r-generalrss 0.1.3
Propagated dependencies: r-rootsolve@1.8.2.4 r-emplik@1.3-2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=generalRSS
Licenses: Expat
Build system: r
Synopsis: Statistical Tools for Balanced and Unbalanced Ranked Set Sampling
Description:

Ranked Set Sampling (RSS) is a stratified sampling method known for its efficiency compared to Simple Random Sampling (SRS). When sample allocation is equal across strata, it is referred to as balanced RSS (BRSS) whereas unequal allocation is called unbalanced RSS (URSS), which is particularly effective for asymmetric or skewed distributions. This package offers practical statistical tools and sampling methods for both BRSS and URSS, emphasizing flexible sampling designs and inference for population means, medians, proportions, and Area Under the Curve (AUC). It incorporates parametric and nonparametric tests, including empirical likelihood ratio (LR) methods. The package provides ranked set sampling methods from a given population, including sampling with imperfect ranking using auxiliary variables. Furthermore, it provides tools for efficient sample allocation in URSS, ensuring greater efficiency than SRS and BRSS. For more details, refer e.g. to Chen et al. (2003) <doi:10.1007/978-0-387-21664-5>, Ahn et al. (2022) <doi:10.1007/978-3-031-14525-4_3>, and Ahn et al. (2024) <doi:10.1111/insr.12589>.

r-getdteval 0.0.2
Propagated dependencies: r-microbenchmark@1.5.0 r-formulaic@0.0.8 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=getDTeval
Licenses: GPL 3
Build system: r
Synopsis: Translating Coding Statements using get() and eval() for Improved Run-Time Coding Efficiency
Description:

The getDTeval() function facilitates the translation of the original coding statement to an optimized form for improved runtime efficiency without compromising on the programmatic coding design. The function can either provide a translation of the coding statement, directly evaluate the translation to return a coding result, or provide both of these outputs.

r-githubr 0.9.1
Propagated dependencies: r-magrittr@2.0.4 r-httr@1.4.7 r-gitcreds@0.1.2 r-gh@1.5.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/fhdsl/githubr
Licenses: GPL 3
Build system: r
Synopsis: Easier to Use API Wrapper for 'GitHub'
Description:

This is a GitHub API wrapper for R. <https://docs.github.com/en/rest> It uses the gh package but has things wrapped up for convenient use cases.

r-gglycan 0.0.3
Propagated dependencies: r-yulab-utils@0.2.1 r-rlang@1.1.6 r-igraph@2.2.1 r-ggtangle@0.0.8 r-ggstar@1.0.6 r-ggrepel@0.9.6 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://cran.r-project.org/package=gglycan
Licenses: Artistic License 2.0
Build system: r
Synopsis: Plot Glycans using 'ggplot2'
Description:

Plot glycans following the Symbol Nomenclature for Glycans (SNFG) using ggplot2'. SNFG provides a standardized visual representation of glycan structures.

r-grnn 0.1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://flow.chasset.net/r-grnn/
Licenses: FSDG-compatible
Build system: r
Synopsis: General regression neural network
Description:

The program GRNN implements the algorithm proposed by Specht (1991).

r-gfiultra 1.0.0
Propagated dependencies: r-sis@0.8-8 r-mvtnorm@1.3-3 r-lazyeval@0.2.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/stla/gfiUltra
Licenses: GPL 3
Build system: r
Synopsis: Generalized Fiducial Inference for Ultrahigh-Dimensional Regression
Description:

Variable selection for ultrahigh-dimensional ("large p small n") linear Gaussian models using a fiducial framework allowing to draw inference on the parameters. Reference: Lai, Hannig & Lee (2015) <doi:10.1080/01621459.2014.931237>.

r-grplasso 0.4-7
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=grplasso
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Fitting User-Specified Models with Group Lasso Penalty
Description:

Fits user-specified (GLM-) models with group lasso penalty.

r-gagblup 1.0
Propagated dependencies: r-ga@3.2.4 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=GAGBLUP
Licenses: GPL 3
Build system: r
Synopsis: Genetic Algorithm Assisted Genomic Best Liner Unbiased Prediction
Description:

This package performs genetic algorithm (Scrucca, L (2013) <doi:10.18637/jss.v053.i04>) assisted genomic best liner unbiased prediction for genomic selection. It also provides a binning method in natural population for genomic selection under the principle of linkage disequilibrium for dimensional reduction.

r-genlib 1.1.10
Propagated dependencies: r-rcpp@1.1.0 r-quadprog@1.5-8 r-matrix@1.7-4 r-lattice@0.22-7 r-kinship2@1.9.6.2 r-foreach@1.5.2 r-doparallel@1.0.17 r-bootstrap@2019.6 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GENLIB
Licenses: GPL 2+
Build system: r
Synopsis: Genealogical Data Analysis
Description:

Genealogical data analysis including descriptive statistics (e.g., kinship and inbreeding coefficients) and gene-dropping simulations. See: "GENLIB: an R package for the analysis of genealogical data" Gauvin et al. (2015) <doi:10.1186/s12859-015-0581-5>.

r-gausssuppression 1.2.3
Propagated dependencies: r-ssbtools@1.8.6 r-rlang@1.1.6 r-regsdc@1.0.0 r-matrix@1.7-4 r-ellipsis@0.3.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/statisticsnorway/ssb-gausssuppression
Licenses: Expat
Build system: r
Synopsis: Tabular Data Suppression using Gaussian Elimination
Description:

This package provides a statistical disclosure control tool to protect tables by suppression using the Gaussian elimination secondary suppression algorithm (Langsrud, 2024) <doi:10.1007/978-3-031-69651-0_6>. A suggestion is to start by working with functions SuppressSmallCounts() and SuppressDominantCells(). These functions use primary suppression functions for the minimum frequency rule and the dominance rule, respectively. Novel functionality for suppression of disclosive cells is also included. General primary suppression functions can be supplied as input to the general working horse function, GaussSuppressionFromData(). Suppressed frequencies can be replaced by synthetic decimal numbers as described in Langsrud (2019) <doi:10.1007/s11222-018-9848-9>.

r-glmmep 1.0-3.1
Propagated dependencies: r-matrixcalc@1.0-6 r-lme4@1.1-37
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=glmmEP
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Linear Mixed Model Analysis via Expectation Propagation
Description:

Approximate frequentist inference for generalized linear mixed model analysis with expectation propagation used to circumvent the need for multivariate integration. In this version, the random effects can be any reasonable dimension. However, only probit mixed models with one level of nesting are supported. The methodology is described in Hall, Johnstone, Ormerod, Wand and Yu (2018) <arXiv:1805.08423v1>.

r-gkwreg 2.1.14
Propagated dependencies: r-tmb@1.9.18 r-rcppeigen@0.3.4.0.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-magrittr@2.0.4 r-gridextra@2.3 r-gkwdist@1.1.2 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/evandeilton/gkwreg
Licenses: Expat
Build system: r
Synopsis: Generalized Kumaraswamy Regression Models for Bounded Data
Description:

This package implements regression models for bounded continuous data in the open interval (0,1) using the five-parameter Generalized Kumaraswamy distribution. Supports modeling all distribution parameters (alpha, beta, gamma, delta, lambda) as functions of predictors through various link functions. Provides efficient maximum likelihood estimation via Template Model Builder ('TMB'), offering comprehensive diagnostics, model comparison tools, and simulation methods. Particularly useful for analyzing proportions, rates, indices, and other bounded response data with complex distributional features not adequately captured by simpler models.

r-gremlin 1.1.0
Propagated dependencies: r-nlme@3.1-168 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/matthewwolak/gremlin
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Mixed-Effects REML Incorporating Generalized Inverses
Description:

Fit linear mixed-effects models using restricted (or residual) maximum likelihood (REML) and with generalized inverse matrices to specify covariance structures for random effects. In particular, the package is suited to fit quantitative genetic mixed models, often referred to as animal models'. Implements the average information algorithm as the main tool to maximize the restricted log-likelihood, but with other algorithms available.

r-groupica 0.1.1
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/sweichwald/groupICA-R
Licenses: AGPL 3
Build system: r
Synopsis: Independent Component Analysis for Grouped Data
Description:

This package contains an implementation of an independent component analysis (ICA) for grouped data. The main function groupICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding for user-specified groups. Additionally, the package contains the function uwedge() which can be used to approximately jointly diagonalize a list of matrices. For more details see the project website <https://sweichwald.de/groupICA/>.

r-gfe 0.1.1
Propagated dependencies: r-teachingsampling@4.1.1 r-dplyr@1.1.4 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=GFE
Licenses: GPL 2+
Build system: r
Synopsis: Gross Flows Estimation under Complex Surveys
Description:

The philosophy in the package is described in Stasny (1988) <doi:10.2307/1391558> and Gutierrez, A., Trujillo, L. & Silva, N. (2014), <ISSN:1492-0921> to estimate the gross flows under complex surveys using a Markov chain approach with non response.

r-glsm 0.0.0.6
Propagated dependencies: r-vgam@1.1-13 r-plyr@1.8.9 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://cran.r-project.org/package=glsm
Licenses: Expat
Build system: r
Synopsis: Saturated Model Log-Likelihood for Multinomial Outcomes
Description:

When the response variable Y takes one of R > 1 values, the function glsm() computes the maximum likelihood estimates (MLEs) of the parameters under four models: null, complete, saturated, and logistic. It also calculates the log-likelihood values for each model. This method assumes independent, non-identically distributed variables. For grouped data with a multinomial outcome, where observations are divided into J populations, the function glsm() provides estimation for any number K of explanatory variables.

r-grc 0.5.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mass@7.3-65 r-igraph@2.2.1 r-grbase@2.0.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://people.math.aau.dk/~sorenh/software/gR/
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries
Description:

Estimation, model selection and other aspects of statistical inference in Graphical Gaussian models with edge and vertex symmetries (Graphical Gaussian models with colours). Documentation about gRc is provided in the paper by Hojsgaard and Lauritzen (2007, <doi:10.18637/jss.v023.i06>) and the paper by Hojsgaard and Lauritzen (2008, <doi:10.1111/j.1467-9868.2008.00666.x>).

r-ggrasp 1.2
Propagated dependencies: r-mixtools@2.0.0.1 r-ggplot2@4.0.1 r-colorspace@2.1-2 r-bgmm@1.8.5 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=ggrasp
Licenses: GPL 2
Build system: r
Synopsis: Gaussian-Based Genome Representative Selector with Prioritization
Description:

Given a group of genomes and their relationship with each other, the package clusters the genomes and selects the most representative members of each cluster. Additional data can be provided to the prioritize certain genomes. The results can be printed out as a list or a new phylogeny with graphs of the trees and distance distributions also available. For detailed introduction see: Thomas H Clarke, Lauren M Brinkac, Granger Sutton, and Derrick E Fouts (2018), GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models, Bioinformatics, bty300, <doi:10.1093/bioinformatics/bty300>.

r-glioblastomaehrsdata 1.1.0
Propagated dependencies: r-tinytex@0.58 r-table1@1.5.1 r-summarytools@1.1.4 r-rmarkdown@2.30 r-ggplot2@4.0.1 r-flextable@0.9.10 r-dataexplorer@0.8.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/Samumar4321/glioblastomaEHRsData
Licenses: GPL 3
Build system: r
Synopsis: Descriptive Analysis on Three Glioblastoma EHRs Datasets
Description:

This package provides functions to load and analyze three open Electronic Health Records (EHRs) datasets of patients diagnosed with glioblastoma, previously released under the Creative Common Attribution 4.0 International (CC BY 4.0) license. Users can generate basic descriptive statistics, frequency tables and save descriptive summary tables, as well as create and export univariate or bivariate plots. The package is designed to work with the included datasets and to facilitate quick exploratory data analysis and reporting. More information about these three datasets of EHRs of patients with glioblastoma can be found in this article: Gabriel Cerono, Ombretta Melaiu, and Davide Chicco, Clinical feature ranking based on ensemble machine learning reveals top survival factors for glioblastoma multiforme', Journal of Healthcare Informatics Research 8, 1-18 (March 2024). <doi:10.1007/s41666-023-00138-1>.

r-ggtreebar 0.1.0
Propagated dependencies: r-treemapify@2.6.0 r-ggplot2@4.0.1 r-ggfittext@0.10.2 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://github.com/hrryt/ggtreebar
Licenses: GPL 3+
Build system: r
Synopsis: Make Treemap Bar Charts with 'ggplot2'
Description:

This package provides ggplot2 geoms analogous to geom_col() and geom_bar() that allow for treemaps using treemapify nested within each bar segment. Also provides geometries for subgroup bordering and text annotation.

r-glvmfit 0.1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=glvmfit
Licenses: GPL 3
Build system: r
Synopsis: Methods to Assess Generalized Latent Variable Model Fit
Description:

This package provides residual global fit indices for generalized latent variable models.

r-gena 1.0.0
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=gena
Licenses: GPL 2+
Build system: r
Synopsis: Genetic Algorithm and Particle Swarm Optimization
Description:

This package implements genetic algorithm and particle swarm algorithm for real-valued functions. Various modifications (including hybridization and elitism) of these algorithms are provided. Implemented functions are based on ideas described in S. Katoch, S. Chauhan, V. Kumar (2020) <doi:10.1007/s11042-020-10139-6> and M. Clerc (2012) <https://hal.archives-ouvertes.fr/hal-00764996>.

r-grattan 2026.1.1
Propagated dependencies: r-magrittr@2.0.4 r-ineq@0.2-13 r-hutilscpp@0.10.10 r-hutils@2.0.0 r-grattaninflators@0.5.7 r-fy@0.4.2 r-forecast@8.24.0 r-fastmatch@1.1-6 r-data-table@1.17.8 r-checkmate@2.3.3 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/HughParsonage/grattan
Licenses: GPL 2
Build system: r
Synopsis: Australian Tax Policy Analysis
Description:

Utilities to cost and evaluate Australian tax policy, including fast projections of personal income tax collections, high-performance tax and transfer calculators, and an interface to common indices from the Australian Bureau of Statistics. Written to support Grattan Institute's Australian Perspectives program, and related projects. Access to the Australian Taxation Office's sample files of personal income tax returns is assumed.

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Total results: 68658