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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-metagear 0.7
Propagated dependencies: r-stringr@1.6.0 r-metafor@4.8-0 r-matrix@1.7-4 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=metagear
Licenses: GPL 2+
Synopsis: Comprehensive Research Synthesis Tools for Systematic Reviews and Meta-Analysis
Description:

Functionalities for facilitating systematic reviews, data extractions, and meta-analyses. It includes a GUI (graphical user interface) to help screen the abstracts and titles of bibliographic data; tools to assign screening effort across multiple collaborators/reviewers and to assess inter- reviewer reliability; tools to help automate the download and retrieval of journal PDF articles from online databases; figure and image extractions from PDFs; web scraping of citations; automated and manual data extraction from scatter-plot and bar-plot images; PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagrams; simple imputation tools to fill gaps in incomplete or missing study parameters; generation of random effects sizes for Hedges d, log response ratio, odds ratio, and correlation coefficients for Monte Carlo experiments; covariance equations for modelling dependencies among multiple effect sizes (e.g., effect sizes with a common control); and finally summaries that replicate analyses and outputs from widely used but no longer updated meta-analysis software (i.e., metawin). Funding for this package was supported by National Science Foundation (NSF) grants DBI-1262545 and DEB-1451031. CITE: Lajeunesse, M.J. (2016) Facilitating systematic reviews, data extraction and meta-analysis with the metagear package for R. Methods in Ecology and Evolution 7, 323-330 <doi:10.1111/2041-210X.12472>.

r-myclim 1.5.0
Propagated dependencies: r-zoo@1.8-14 r-vroom@1.6.6 r-viridis@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-purrr@1.2.0 r-progress@1.2.3 r-plotly@4.11.0 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://labgis.ibot.cas.cz/myclim/index.html
Licenses: GPL 2+
Synopsis: Microclimatic Data Processing
Description:

Handling the microclimatic data in R. The myClim workflow begins at the reading data primary from microclimatic dataloggers, but can be also reading of meteorological station data from files. Cleaning time step, time zone settings and metadata collecting is the next step of the work flow. With myClim tools one can crop, join, downscale, and convert microclimatic data formats, sort them into localities, request descriptive characteristics and compute microclimatic variables. Handy plotting functions are provided with smart defaults.

r-multiclasspairs 0.4.3
Propagated dependencies: r-rdist@0.0.5 r-ranger@0.17.0 r-e1071@1.7-16 r-dunn-test@1.3.6 r-caret@7.0-1 r-boruta@9.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/NourMarzouka/multiclassPairs
Licenses: GPL 2+
Synopsis: Build MultiClass Pair-Based Classifiers using TSPs or RF
Description:

This package provides a toolbox to train a single sample classifier that uses in-sample feature relationships. The relationships are represented as feature1 < feature2 (e.g. gene1 < gene2). We provide two options to go with. First is based on switchBox package which uses Top-score pairs algorithm. Second is a novel implementation based on random forest algorithm. For simple problems we recommend to use one-vs-rest using TSP option due to its simplicity and for being easy to interpret. For complex problems RF performs better. Both lines filter the features first then combine the filtered features to make the list of all the possible rules (i.e. rule1: feature1 < feature2, rule2: feature1 < feature3, etc...). Then the list of rules will be filtered and the most important and informative rules will be kept. The informative rules will be assembled in an one-vs-rest model or in an RF model. We provide a detailed description with each function in this package to explain the filtration and training methodology in each line. Reference: Marzouka & Eriksson (2021) <doi:10.1093/bioinformatics/btab088>.

r-miivefa 0.1.2
Propagated dependencies: r-miivsem@0.5.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/lluo0/MIIVefa/
Licenses: Expat
Synopsis: Exploratory Factor Analysis Using Model Implied Instrumental Variables
Description:

Data-driven approach for Exploratory Factor Analysis (EFA) that uses Model Implied Instrumental Variables (MIIVs). The method starts with a one factor model and arrives at a suggested model with enhanced interpretability that allows cross-loadings and correlated errors.

r-mram 0.2.1
Propagated dependencies: r-rann@2.6.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MRAM
Licenses: GPL 2
Synopsis: Multivariate Regression Association Measure
Description:

Implementations of an estimator for the multivariate regression association measure (MRAM) proposed in Shih and Chen (2025) <in revision> and its associated variable selection algorithm. The MRAM quantifies the predictability of a random vector Y from a random vector X given a random vector Z. It takes the maximum value 1 if and only if Y is almost surely a measurable function of X and Z, and the minimum value of 0 if Y is conditionally independent of X given Z. The MRAM generalizes the Kendall's tau copula correlation ratio proposed in Shih and Emura (2021) <doi:10.1016/j.jmva.2020.104708> by employing the spatial sign function. The estimator is based on the nearest neighbor method, and the associated variable selection algorithm is adapted from the feature ordering by conditional independence (FOCI) algorithm of Azadkia and Chatterjee (2021) <doi:10.1214/21-AOS2073>. For further details, see the paper Shih and Chen (2025) <in revision>.

r-metapro 1.5.11
Propagated dependencies: r-metap@1.12
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=metapro
Licenses: GPL 2+
Synopsis: Robust P-Value Combination Methods
Description:

The meta-analysis is performed to increase the statistical power by integrating the results from several experiments. The p-values are often combined in meta-analysis when the effect sizes are not available. The metapro R package provides not only traditional methods (Becker BJ (1994, ISBN:0-87154-226-9), Mosteller, F. & Bush, R.R. (1954, ISBN:0201048523) and Lancaster HO (1949, ISSN:00063444)), but also new method named weighted Fisherâ s method we developed. While the (weighted) Z-method is suitable for finding features effective in most experiments, (weighted) Fisherâ s method is useful for detecting partially associated features. Thus, the users can choose the function based on their purpose. Yoon et al. (2021) "Powerful p-value combination methods to detect incomplete association" <doi:10.1038/s41598-021-86465-y>.

r-midas 1.0.1
Propagated dependencies: r-xml2@1.5.0 r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=midas
Licenses: GPL 3
Synopsis: Turn HTML 'Shiny'
Description:

This package contains functions for converting existing HTML/JavaScript source into equivalent shiny functions. Bootstraps the process of making new shiny functions by allowing us to turn HTML snippets directly into R functions.

r-mlrv 0.1.2
Propagated dependencies: r-xtable@1.8-4 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-mathjaxr@1.8-0 r-magrittr@2.0.4 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mlrv
Licenses: Expat
Synopsis: Long-Run Variance Estimation in Time Series Regression
Description:

Plug-in and difference-based long-run covariance matrix estimation for time series regression. Two applications of hypothesis testing are also provided. The first one is for testing for structural stability in coefficient functions. The second one is aimed at detecting long memory in time series regression. Lujia Bai and Weichi Wu (2024)<doi:10.3150/23-BEJ1680> Zhou Zhou and Wei Biao Wu(2010)<doi:10.1111/j.1467-9868.2010.00743.x> Jianqing Fan and Wenyang Zhang<doi:10.1214/aos/1017939139> Lujia Bai and Weichi Wu(2024)<doi:10.1093/biomet/asae013> Dimitris N. Politis, Joseph P. Romano, Michael Wolf(1999)<doi:10.1007/978-1-4612-1554-7> Weichi Wu and Zhou Zhou(2018)<doi:10.1214/17-AOS1582>.

r-mitre 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-rjsonio@2.0.0 r-plyr@1.8.9 r-jsonlite@2.0.0 r-igraph@2.2.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/motherhack3r/mitre
Licenses: CC0
Synopsis: Cybersecurity MITRE Standards Data and Digraphs
Description:

Extract, transform and load MITRE standards. This package gives you an approach to cybersecurity data sets. All data sets are build on runtime downloading raw data from MITRE public services. MITRE <https://www.mitre.org/> is a government-funded research organization based in Bedford and McLean. Current version includes most used standards as data frames. It also provide a list of nodes and edges with all relationships.

r-matsindf 0.4.11
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-openxlsx2@1.22 r-matsbyname@0.6.13 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/MatthewHeun/matsindf
Licenses: Expat
Synopsis: Matrices in Data Frames
Description:

This package provides functions to collapse a tidy data frame into matrices in a data frame and expand a data frame of matrices into a tidy data frame.

r-moodler 1.0.1
Propagated dependencies: r-usethis@3.2.1 r-tidytext@0.4.3 r-stringr@1.6.0 r-scales@1.4.0 r-rsqlite@2.4.4 r-rpostgres@1.4.8 r-rmariadb@1.3.4 r-rlang@1.1.6 r-lifecycle@1.0.4 r-glue@1.8.0 r-ggwordcloud@0.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-dbi@1.2.3 r-config@0.3.2 r-cli@3.6.5 r-anytime@0.3.12
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/chi2labs/moodleR
Licenses: Expat
Synopsis: Helper Functions to Work with 'Moodle' Data
Description:

This package provides a collection of functions to connect to a Moodle database, cache relevant tables locally and generate learning analytics. Moodle is an open source Learning Management System (LMS) developed by MoodleHQ. For more information about Moodle, visit <https://moodle.org>.

r-mpge 1.0.0
Propagated dependencies: r-purrr@1.2.0 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ArunabhaCodes/MPGE
Licenses: GPL 3
Synopsis: Two-Step Approach to Testing Overall Effect of Gene-Environment Interaction for Multiple Phenotypes
Description:

Interaction between a genetic variant (e.g., a single nucleotide polymorphism) and an environmental variable (e.g., physical activity) can have a shared effect on multiple phenotypes (e.g., blood lipids). We implement a two-step method to test for an overall interaction effect on multiple phenotypes. In first step, the method tests for an overall marginal genetic association between the genetic variant and the multivariate phenotype. The genetic variants which show an evidence of marginal overall genetic effect in the first step are prioritized while testing for an overall gene-environment interaction effect in the second step. Methodology is available from: A Majumdar, KS Burch, S Sankararaman, B Pasaniuc, WJ Gauderman, JS Witte (2020) <doi:10.1101/2020.07.06.190256>.

r-mod09nrt 0.14
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mod09nrt
Licenses: GPL 2+
Synopsis: Extraction of Bands from MODIS Surface Reflectance Product MOD09 NRT
Description:

Package for processing downloaded MODIS Surface reflectance Product HDF files. Specifically, MOD09 surface reflectance product files, and the associated MOD03 geolocation files (for MODIS-TERRA). The package will be most effective if the user installs MRTSwath (MODIS Reprojection Tool for swath products; <https://lpdaac.usgs.gov/tools/modis_reprojection_tool_swath>, and adds the directory with the MRTSwath executable to the default R PATH by editing ~/.Rprofile.

r-macro 0.1.5
Propagated dependencies: r-fmtr@1.7.0 r-crayon@1.5.3 r-common@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://macro.r-sassy.org
Licenses: CC0
Synopsis: Macro Language for 'R' Programs
Description:

This package provides a macro language for R programs, which provides a macro facility similar to SAS®'. This package contains basic macro capabilities like defining macro variables, executing conditional logic, and defining macro functions.

r-mbnmadose 0.5.0
Dependencies: jags@4.3.1
Propagated dependencies: r-scales@1.4.0 r-rjags@4-17 r-reshape2@1.4.5 r-rdpack@2.6.4 r-r2jags@0.8-9 r-magrittr@2.0.4 r-igraph@2.2.1 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://hugaped.github.io/MBNMAdose/
Licenses: GPL 3
Synopsis: Dose-Response MBNMA Models
Description:

Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that incorporate multiple doses within an agent by modelling different dose-response functions, as described by Mawdsley et al. (2016) <doi:10.1002/psp4.12091>. By modelling dose-response relationships this can connect networks of evidence that might otherwise be disconnected, and can improve precision on treatment estimates. Several common dose-response functions are provided; others may be added by the user. Various characteristics and assumptions can be flexibly added to the models, such as shared class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects models and/or by node-splitting at the treatment level.

r-molgenisauth 1.0.0
Propagated dependencies: r-urltools@1.7.3.1 r-httr2@1.2.1 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/molgenis/molgenis-r-auth/
Licenses: GPL 3
Synopsis: 'OpenID Connect' Discovery and Authentication
Description:

Discover OpenID Connect endpoints and authenticate using device flow. Used by MOLGENIS packages.

r-mvst 1.1.1
Dependencies: gsl@2.8
Propagated dependencies: r-mvtnorm@1.3-3 r-mnormt@2.1.1 r-mcmcpack@1.7-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mvst
Licenses: GPL 3
Synopsis: Bayesian Inference for the Multivariate Skew-t Model
Description:

Estimates the multivariate skew-t and nested models, as described in the articles Liseo, B., Parisi, A. (2013). Bayesian inference for the multivariate skew-normal model: a population Monte Carlo approach. Comput. Statist. Data Anal. <doi:10.1016/j.csda.2013.02.007> and in Parisi, A., Liseo, B. (2017). Objective Bayesian analysis for the multivariate skew-t model. Statistical Methods & Applications <doi: 10.1007/s10260-017-0404-0>.

r-mllmcelltype 1.3.2
Propagated dependencies: r-r6@2.6.1 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cafferyang.com/mLLMCelltype/
Licenses: Expat
Synopsis: Cell Type Annotation Using Large Language Models
Description:

Automated cell type annotation for single-cell RNA sequencing data using consensus predictions from multiple large language models (LLMs). LLMs are artificial intelligence models trained on vast text corpora to understand and generate human-like text. This package integrates with Seurat objects and provides uncertainty quantification for annotations. Supports various LLM providers including OpenAI', Anthropic', and Google'. The package leverages these models through their respective APIs (Application Programming Interfaces) <https://platform.openai.com/docs>, <https://docs.anthropic.com/>, and <https://ai.google.dev/gemini-api/docs>. For details see Yang et al. (2025) <doi:10.1101/2025.04.10.647852>.

r-mmabig 3.2-0
Propagated dependencies: r-survival@3.8-3 r-mma@10.8-1 r-gplots@3.2.0 r-glmnet@4.1-10 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.r-project.org
Licenses: GPL 2+
Synopsis: Multiple Mediation Analysis for Big Data Sets
Description:

Used for general multiple mediation analysis with big data sets.

r-minigui 0.8-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=miniGUI
Licenses: FSDG-compatible
Synopsis: Tcl/Tk Quick and Simple Function GUI
Description:

Quick and simple Tcl/Tk Graphical User Interface to call functions. Also comprises a very simple experimental GUI framework.

r-mapi 1.1.4
Propagated dependencies: r-sf@1.0-23 r-s2@1.1.9 r-rcpp@1.1.0 r-foreach@1.5.2 r-fmesher@0.5.0 r-doparallel@1.0.17 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www1.montpellier.inrae.fr/CBGP/software/MAPI/
Licenses: GPL 3+
Synopsis: Mapping Averaged Pairwise Information
Description:

Mapping Averaged Pairwise Information (MAPI) is an exploratory method providing graphical representations summarizing the spatial variation of pairwise metrics (eg. distance, similarity coefficient, ...) computed between georeferenced samples.

r-mixedlsr 0.1.0
Propagated dependencies: r-purrr@1.2.0 r-mass@7.3-65 r-grpreg@3.5.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://alexanderjwhite.github.io/mixedLSR/
Licenses: Expat
Synopsis: Mixed, Low-Rank, and Sparse Multivariate Regression on High-Dimensional Data
Description:

Mixed, low-rank, and sparse multivariate regression ('mixedLSR') provides tools for performing mixture regression when the coefficient matrix is low-rank and sparse. mixedLSR allows subgroup identification by alternating optimization with simulated annealing to encourage global optimum convergence. This method is data-adaptive, automatically performing parameter selection to identify low-rank substructures in the coefficient matrix.

r-managelocalrepo 0.1.5
Propagated dependencies: r-stringr@1.6.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=managelocalrepo
Licenses: GPL 2
Synopsis: Manage a CRAN-Style Local Repository
Description:

This will allow easier management of a CRAN-style repository on local networks (i.e. not on CRAN). This might be necessary where hosted packages contain intellectual property owned by a corporation.

r-mazamaspatialplots 0.3.0
Propagated dependencies: r-tmap@4.2 r-sf@1.0-23 r-rlang@1.1.6 r-mazamaspatialutils@0.8.7 r-mazamacoreutils@0.5.3 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/MazamaScience/MazamaSpatialPlots
Licenses: GPL 3
Synopsis: Thematic Plots for Mazama Spatial Datasets
Description:

This package provides a suite of convenience functions for generating US state and county thematic maps using datasets from the MazamaSpatialUtils package.

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