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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-micvar 0.1.0
Propagated dependencies: r-rdpack@2.6.4 r-matrixcalc@1.0-6 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=micvar
Licenses: GPL 3+
Build system: r
Synopsis: Order Selection in Vector Autoregression by Mean Square Information Criteria
Description:

This package implements order selection for Vector Autoregressive (VAR) models using the Mean Square Information Criterion (MIC). Unlike standard methods such as AIC and BIC, MIC is likelihood-free. This method consistently estimates VAR order and has robust performance under model misspecification. For more details, see Hellstern and Shojaie (2025) <doi:10.48550/arXiv.2511.19761>.

r-matrixnormal 0.1.2
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=matrixNormal
Licenses: GPL 3
Build system: r
Synopsis: The Matrix Normal Distribution
Description:

Computes densities, probabilities, and random deviates of the Matrix Normal (Pocuca et al. (2019) <doi:10.48550/arXiv.1910.02859>). Also includes simple but useful matrix functions. See the vignette for more information.

r-microsynth 2.0.51
Propagated dependencies: r-survey@4.4-8 r-pracma@2.4.6 r-lowrankqp@1.0.6 r-kernlab@0.9-33
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=microsynth
Licenses: GPL 3
Build system: r
Synopsis: Synthetic Control Methods with Micro- And Meso-Level Data
Description:

This package provides a generalization of the Synth package that is designed for data at a more granular level (e.g., micro-level). Provides functions to construct weights (including propensity score-type weights) and run analyses for synthetic control methods with micro- and meso-level data; see Robbins, Saunders, and Kilmer (2017) <doi:10.1080/01621459.2016.1213634> and Robbins and Davenport (2021) <doi:10.18637/jss.v097.i02>.

r-mdgc 0.1.7
Propagated dependencies: r-testthat@3.3.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-psqn@0.3.2 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/boennecd/mdgc
Licenses: GPL 2
Build system: r
Synopsis: Missing Data Imputation Using Gaussian Copulas
Description:

This package provides functions to impute missing values using Gaussian copulas for mixed data types as described by Christoffersen et al. (2021) <arXiv:2102.02642>. The method is related to Hoff (2007) <doi:10.1214/07-AOAS107> and Zhao and Udell (2019) <arXiv:1910.12845> but differs by making a direct approximation of the log marginal likelihood using an extended version of the Fortran code created by Genz and Bretz (2002) <doi:10.1198/106186002394> in addition to also support multinomial variables.

r-mplusautomation 1.2
Propagated dependencies: r-xtable@1.8-4 r-texreg@1.39.5 r-plyr@1.8.9 r-pander@0.6.6 r-lattice@0.22-7 r-gsubfn@0.7 r-ggplot2@4.0.1 r-fastdummies@1.7.5 r-digest@0.6.39 r-data-table@1.17.8 r-coda@0.19-4.1 r-checkmate@2.3.3 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://michaelhallquist.github.io/MplusAutomation/
Licenses: LGPL 3
Build system: r
Synopsis: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus
Description:

Leverages the R language to automate latent variable model estimation and interpretation using Mplus', a powerful latent variable modeling program developed by Muthen and Muthen (<https://www.statmodel.com>). Specifically, this package provides routines for creating related groups of models, running batches of models, and extracting and tabulating model parameters and fit statistics.

r-mapmixture 1.2.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-sf@1.0-23 r-rnaturalearthdata@1.0.0 r-rlang@1.1.6 r-purrr@1.2.0 r-ggspatial@1.1.10 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/Tom-Jenkins/mapmixture
Licenses: GPL 3+
Build system: r
Synopsis: Spatial Visualisation of Admixture on a Projected Map
Description:

Visualise admixture as pie charts on a projected map, admixture as traditional structure barplots or facet barplots, and scatter plots from genotype principal components analysis. A shiny app allows users to create admixture maps interactively. Jenkins TL (2024) <doi:10.1111/1755-0998.13943>.

r-mgcviz 0.2.1
Propagated dependencies: r-viridis@0.6.5 r-qgam@2.0.0 r-plyr@1.8.9 r-mgcv@1.9-4 r-matrixstats@1.5.0 r-kernsmooth@2.23-26 r-gridextra@2.3 r-ggplot2@4.0.1 r-ggally@2.4.0 r-gamm4@0.2-7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mfasiolo/mgcViz
Licenses: GPL 3
Build system: r
Synopsis: Visualisations for Generalized Additive Models
Description:

Extension of the mgcv package, providing visual tools for Generalized Additive Models that exploit the additive structure of such models, scale to large data sets and can be used in conjunction with a wide range of response distributions. The focus is providing visual methods for better understanding the model output and for aiding model checking and development beyond simple exponential family regression. The graphical framework is based on the layering system provided by ggplot2'.

r-mva 1.0-9
Propagated dependencies: r-hsaur2@1.1-21
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://dx.doi.org/10.1007/978-1-4419-9650-3
Licenses: GPL 2
Build system: r
Synopsis: An Introduction to Applied Multivariate Analysis with R
Description:

Functions, data sets, analyses and examples from the book `An Introduction to Applied Multivariate Analysis with R (Brian S. Everitt and Torsten Hothorn, Springer, 2011).

r-motherduck 0.2.1
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-janitor@2.2.1 r-httr2@1.2.1 r-glue@1.8.0 r-duckdb@1.4.2 r-dplyr@1.1.4 r-dbplyr@2.5.1 r-dbi@1.2.3 r-cli@3.6.5 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://usrbinr.github.io/motherduck/
Licenses: Expat
Build system: r
Synopsis: Utilities for Managing a 'Motherduck' Database
Description:

This package provides helper functions, metadata utilities, and workflows for administering and managing databases on the Motherduck cloud platform. Some features require a Motherduck account (<https://motherduck.com/>).

r-manta 1.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/dgarrimar/manta
Licenses: GPL 3
Build system: r
Synopsis: Multivariate Asymptotic Non-Parametric Test of Association
Description:

The Multivariate Asymptotic Non-parametric Test of Association (MANTA) enables non-parametric, asymptotic P-value computation for multivariate linear models. MANTA relies on the asymptotic null distribution of the PERMANOVA test statistic. P-values are computed using a highly accurate approximation of the corresponding cumulative distribution function. Garrido-Martà n et al. (2022) <doi:10.1101/2022.06.06.493041>.

r-minb 0.1.0
Propagated dependencies: r-pscl@1.5.9 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=minb
Licenses: GPL 3
Build system: r
Synopsis: Multiple-Inflated Negative Binomial Model
Description:

Count data is prevalent and informative, with widespread application in many fields such as social psychology, personality, and public health. Classical statistical methods for the analysis of count outcomes are commonly variants of the log-linear model, including Poisson regression and Negative Binomial regression. However, a typical problem with count data modeling is inflation, in the sense that the counts are evidently accumulated on some integers. Such an inflation problem could distort the distribution of the observed counts, further bias estimation and increase error, making the classic methods infeasible. Traditional inflated value selection methods based on histogram inspection are easy to neglect true points and computationally expensive in addition. Therefore, we propose a multiple-inflated negative binomial model to handle count data modeling with multiple inflated values, achieving data-driven inflated value selection. The proposed approach provides simultaneous identification of important regression predictors on the target count response as well. More details about the proposed method are described in Li, Y., Wu, M., Wu, M., & Ma, S. (2023) <arXiv:2309.15585>.

r-medianews 0.2.1
Propagated dependencies: r-xml2@1.5.0 r-stopwords@2.3 r-rvest@1.0.5 r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MediaNews
Licenses: LGPL 3
Build system: r
Synopsis: Media News Extraction for Text Analysis
Description:

Extract textual data from different media channels through its source based on users choice of keywords. These data can be used to perform text analysis to identify patterns in respective media reporting. The media channels used in this package are print media. The data (or news) used are publicly available to consumers.

r-maxaltall 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-magrittr@2.0.4 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: https://cran.r-project.org/package=maxaltall
Licenses: GPL 3+
Build system: r
Synopsis: 'FASTA' ML and ‘altall’ Sequences from IQ-TREE .state Files
Description:

Takes a .state file generated by IQ-TREE as an input and, for each ancestral node present in the file, generates a FASTA-formatted maximum likelihood (ML) sequence as well as an âAltAllâ sequence in which uncertain sites, determined by the two parameters thres_1 and thres_2, have the maximum likelihood state swapped with the next most likely state as described in Geeta N. Eick, Jamie T. Bridgham, Douglas P. Anderson, Michael J. Harms, and Joseph W. Thornton (2017), "Robustness of Reconstructed Ancestral Protein Functions to Statistical Uncertainty" <doi:10.1093/molbev/msw223>.

r-mutualinf 2.0.4
Propagated dependencies: r-runner@0.4.4 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/RafaelFuentealbaC/mutualinf
Licenses: GPL 3
Build system: r
Synopsis: Computation and Decomposition of the Mutual Information Index
Description:

The Mutual Information Index (M) introduced to social science literature by Theil and Finizza (1971) <doi:10.1080/0022250X.1971.9989795> is a multigroup segregation measure that is highly decomposable and that according to Frankel and Volij (2011) <doi:10.1016/j.jet.2010.10.008> and Mora and Ruiz-Castillo (2011) <doi:10.1111/j.1467-9531.2011.01237.x> satisfies the Strong Unit Decomposability and Strong Group Decomposability properties. This package allows computing and decomposing the total index value into its "between" and "within" terms. These last terms can also be decomposed into their contributions, either by group or unit characteristics. The factors that produce each "within" term can also be displayed at the user's request. The results can be computed considering a variable or sets of variables that define separate clusters.

r-missplot 0.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=Missplot
Licenses: GPL 3
Build system: r
Synopsis: Missing Plot Technique in Design of Experiment
Description:

This package provides a system for testing differential effects among treatments in case of Randomised Block Design and Latin Square Design when there is one missing observation. Methods for this process are as described in A.M.Gun,M.K.Gupta and B.Dasgupta(2019,ISBN:81-87567-81-3).

r-mrct 0.0.1.0
Propagated dependencies: r-robustbase@0.99-6 r-reshape2@1.4.5 r-rdpack@2.6.4 r-ggplot2@4.0.1 r-fdapace@0.6.0 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mrct
Licenses: GPL 2+
Build system: r
Synopsis: Outlier Detection of Functional Data Based on the Minimum Regularized Covariance Trace Estimator
Description:

Detect outlying observations in functional data sets based on the minimum regularized covariance trace (MRCT) estimator. Includes implementation of Oguamalam et al. (2023) <arXiv:2307.13509>.

r-mirkat 1.2.3
Propagated dependencies: r-survival@3.8-3 r-quantreg@6.1 r-permute@0.9-8 r-pearsonds@1.3.2 r-mixtools@2.0.0.1 r-matrix@1.7-4 r-mass@7.3-65 r-lme4@1.1-37 r-gunifrac@1.9 r-compquadform@1.4.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MiRKAT
Licenses: GPL 2+
Build system: r
Synopsis: Microbiome Regression-Based Kernel Association Tests
Description:

Test for overall association between microbiome composition data and phenotypes via phylogenetic kernels. The phenotype can be univariate continuous or binary (Zhao et al. (2015) <doi:10.1016/j.ajhg.2015.04.003>), survival outcomes (Plantinga et al. (2017) <doi:10.1186/s40168-017-0239-9>), multivariate (Zhan et al. (2017) <doi:10.1002/gepi.22030>) and structured phenotypes (Zhan et al. (2017) <doi:10.1111/biom.12684>). The package can also use robust regression (unpublished work) and integrated quantile regression (Wang et al. (2021) <doi:10.1093/bioinformatics/btab668>). In each case, the microbiome community effect is modeled nonparametrically through a kernel function, which can incorporate phylogenetic tree information.

r-mlpugs 0.2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/bearloga/MLPUGS
Licenses: Expat
Build system: r
Synopsis: Multi-Label Prediction Using Gibbs Sampling (and Classifier Chains)
Description:

An implementation of classifier chains (CC's) for multi-label prediction. Users can employ an external package (e.g. randomForest', C50'), or supply their own. The package can train a single set of CC's or train an ensemble of CC's -- in parallel if running in a multi-core environment. New observations are classified using a Gibbs sampler since each unobserved label is conditioned on the others. The package includes methods for evaluating the predictions for accuracy and aggregating across iterations and models to produce binary or probabilistic classifications.

r-mrangr 1.0.1
Propagated dependencies: r-terra@1.8-86 r-rcolorbrewer@1.1-3 r-rangr@1.0.9 r-mgcv@1.9-4 r-gstat@2.1-4 r-fieldsimr@1.4.0 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=mrangr
Licenses: Expat
Build system: r
Synopsis: Mechanistic Metacommunity Simulator
Description:

Flexible, mechanistic, and spatially explicit simulator of metacommunities. It extends our previous package - rangr (see <https://github.com/ropensci/rangr>), which implemented a mechanistic virtual species simulator integrating population dynamics and dispersal. The mrangr package adds the ability to simulate multiple species interacting through an asymmetric matrix of pairwise relationships, allowing users to model all types of biotic interactions â competitive, facilitative, or neutral â within spatially explicit virtual environments. This work was supported by the National Science Centre, Poland, grant no. 2018/29/B/NZ8/00066 and the PoznaÅ Supercomputing and Networking Centre (grant no. pl0090-01).

r-morphomenses 1.0.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: <https://github.com/ClancyLabUIUC/moRphomenses>
Licenses: GPL 3+
Build system: r
Synopsis: Geometric Morphometric Tools to Align, Scale, and Compare "Shape" of Menstrual Cycle Hormones
Description:

Mitteroecker & Gunz (2009) <doi:10.1007/s11692-009-9055-x> describe how geometric morphometric methods allow researchers to quantify the size and shape of physical biological structures. We provide tools to extend geometric morphometric principles to the study of non-physical structures, hormone profiles, as outlined in Ehrlich et al (2021) <doi:10.1002/ajpa.24514>. Easily transform daily measures into multivariate landmark-based data. Includes custom functions to apply multivariate methods for data exploration as well as hypothesis testing. Also includes shiny web app to streamline data exploration. Developed to study menstrual cycle hormones but functions have been generalized and should be applicable to any biomarker over any time period.

r-marqlevalg 2.0.8
Propagated dependencies: 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=marqLevAlg
Licenses: GPL 2+
Build system: r
Synopsis: Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm
Description:

This algorithm provides a numerical solution to the problem of unconstrained local minimization (or maximization). It is particularly suited for complex problems and more efficient than the Gauss-Newton-like algorithm when starting from points very far from the final minimum (or maximum). Each iteration is parallelized and convergence relies on a stringent stopping criterion based on the first and second derivatives. See Philipps et al, 2021 <doi:10.32614/RJ-2021-089>.

r-mongolstats 0.1.1
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-stringdist@0.9.15 r-sf@1.0-23 r-rappdirs@0.3.3 r-purrr@1.2.0 r-memoise@2.0.1 r-jsonlite@2.0.0 r-httr2@1.2.1 r-dplyr@1.1.4 r-curl@7.0.0 r-cachem@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://temuulene.github.io/mongolstats/
Licenses: Expat
Build system: r
Synopsis: Mongolian 'NSO' 'PXWeb' Data and Boundaries (Tidy Client)
Description:

This package provides a tidyverse'-friendly client for the National Statistics Office of Mongolia PXWeb API <https://data.1212.mn/> with helpers to discover tables, variables, and fetch statistical data. Also includes utilities to retrieve Mongolia administrative boundaries (ADM0-ADM2) as sf objects from open sources for mapping and spatial analysis.

r-multivariaterandomforest 1.1.5
Propagated dependencies: r-rcpp@1.1.0 r-bootstrap@2019.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultivariateRandomForest
Licenses: GPL 2+
Build system: r
Synopsis: Models Multivariate Cases Using Random Forests
Description:

Models and predicts multiple output features in single random forest considering the linear relation among the output features, see details in Rahman et al (2017)<doi:10.1093/bioinformatics/btw765>.

r-matrixprofile 0.5.0
Propagated dependencies: r-zoo@1.8-14 r-ttr@0.24.4 r-signal@1.8-1 r-fftw@1.0-9
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ainsuotain/matrixprofile
Licenses: GPL 3
Build system: r
Synopsis: Matrix Profile
Description:

This package provides a simple and the early stage package for matrix profile based on the paper of Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, and Eamonn Keogh (2016) <DOI:10.1109/ICDM.2016.0179>. This package calculates all-pairs-similarity for a given window size for time series data.

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Total results: 69112