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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-mmc 0.0.3
Propagated dependencies: r-survival@3.8-3 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=mmc
Licenses: GPL 3+
Build system: r
Synopsis: Multivariate Measurement Error Correction
Description:

This package provides routines for multivariate measurement error correction. Includes procedures for linear, logistic and Cox regression models. Bootstrapped standard errors and confidence intervals can be obtained for corrected estimates.

r-mvshapirotest 1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mvShapiroTest
Licenses: GPL 3+
Build system: r
Synopsis: Generalized Shapiro-Wilk test for multivariate normality
Description:

This package implements the generalization of the Shapiro-Wilk test for multivariate normality proposed by Villasenor-Alva and Gonzalez-Estrada (2009).

r-mgm 1.2-15
Propagated dependencies: r-stringr@1.6.0 r-qgraph@1.9.8 r-hmisc@5.2-4 r-gtools@3.9.5 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.jstatsoft.org/article/view/v093i08
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Time-Varying k-Order Mixed Graphical Models
Description:

Estimation of k-Order time-varying Mixed Graphical Models and mixed VAR(p) models via elastic-net regularized neighborhood regression. For details see Haslbeck & Waldorp (2020) <doi:10.18637/jss.v093.i08>.

r-mvnmle 0.1-11.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/indenkun/mvnmle
Licenses: GPL 2+
Build system: r
Synopsis: ML Estimation for Multivariate Normal Data with Missing Values
Description:

Finds the Maximum Likelihood (ML) Estimate of the mean vector and variance-covariance matrix for multivariate normal data with missing values.

r-muchpoint 0.6.4
Propagated dependencies: r-shiny@1.11.1 r-rcpp@1.1.0 r-matrix@1.7-4 r-capushe@1.1.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/Lionning/MuChPoint
Licenses: GPL 2
Build system: r
Synopsis: Multiple Change Point
Description:

Nonparametric approach to estimate the location of block boundaries (change-points) of non-overlapping blocks in a random symmetric matrix which consists of random variables whose distribution changes from block to block. BRAULT Vincent, OUADAH Sarah, SANSONNET Laure and LEVY-LEDUC Celine (2017) <doi:10.1016/j.jmva.2017.12.005>.

r-mba 0.1-2
Propagated dependencies: r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MBA
Licenses: GPL 2+
Build system: r
Synopsis: Multilevel B-Spline Approximation
Description:

This package provides functions to interpolate irregularly and regularly spaced data using Multilevel B-spline Approximation (MBA). Functions call portions of the SINTEF Multilevel B-spline Library written by à yvind Hjelle which implements methods developed by Lee, Wolberg and Shin (1997; <doi:10.1109/2945.620490>).

r-metr 0.18.3
Propagated dependencies: r-stringr@1.6.0 r-sf@1.0-23 r-scales@1.4.0 r-rlang@1.1.6 r-purrr@1.2.0 r-plyr@1.8.9 r-memoise@2.0.1 r-lubridate@1.9.4 r-isoband@0.2.7 r-gtable@0.3.6 r-ggplot2@4.0.1 r-formula-tools@1.7.1 r-formula@1.2-5 r-digest@0.6.39 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://eliocamp.github.io/metR/
Licenses: GPL 3
Build system: r
Synopsis: Tools for Easier Analysis of Meteorological Fields
Description:

Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends ggplot2 for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.

r-mgi-report-reader 0.1.3
Propagated dependencies: r-vroom@1.6.6 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-memoise@2.0.1 r-httr2@1.2.1 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://www.pattern.institute/mgi.report.reader/
Licenses: Expat
Build system: r
Synopsis: Read Mouse Genome Informatics Reports
Description:

This package provides readers for easy and consistent importing of Mouse Genome Informatics (MGI) report files: <https://www.informatics.jax.org/downloads/reports/index.html>. These data are provided by Baldarelli RM, Smith CL, Ringwald M, Richardson JE, Bult CJ, Mouse Genome Informatics Group (2024) <doi:10.1093/genetics/iyae031>.

r-mstudentd 1.1.2
Propagated dependencies: r-rgl@1.3.31 r-mass@7.3-65 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://forgemia.inra.fr/imhorphen/mstudentd
Licenses: GPL 3+
Build system: r
Synopsis: Multivariate t Distribution
Description:

Distance between multivariate t distributions, as presented by N. Bouhlel and D. Rousseau (2023) <doi:10.1109/LSP.2023.3324594>.

r-manymodelr 0.4.0
Propagated dependencies: r-usethis@3.2.1 r-testthat@3.3.0 r-stringr@1.6.0 r-metrics@0.1.4 r-lme4@1.1-37 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/Nelson-Gon/manymodelr
Licenses: GPL 2
Build system: r
Synopsis: Build and Tune Several Models
Description:

Frequently one needs a convenient way to build and tune several models in one go.The goal is to provide a number of machine learning convenience functions. It provides the ability to build, tune and obtain predictions of several models in one function. The models are built using functions from caret with easier to read syntax. Kuhn(2014) <doi:10.48550/arXiv.1405.6974>.

r-mlr3spatial 0.6.1
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-r6@2.6.1 r-mlr3misc@0.19.0 r-mlr3@1.2.0 r-lgr@0.5.0 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mlr3spatial.mlr-org.com
Licenses: LGPL 3
Build system: r
Synopsis: Support for Spatial Objects Within the 'mlr3' Ecosystem
Description:

Extends the mlr3 ML framework with methods for spatial objects. Data storage and prediction are supported for packages terra', raster and stars'.

r-mixedpsy 1.3.0
Propagated dependencies: r-tidyselect@1.2.1 r-rlang@1.1.6 r-purrr@1.2.0 r-mnormt@2.1.1 r-matrix@1.7-4 r-magrittr@2.0.4 r-lme4@1.1-37 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-brglm@0.7.3 r-boot@1.3-32 r-beepr@2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mixedpsychophysics.wordpress.com
Licenses: GPL 2+
Build system: r
Synopsis: Statistical Tools for the Analysis of Psychophysical Data
Description:

This package provides tools for the analysis of psychophysical data in R. This package allows to estimate the Point of Subjective Equivalence (PSE) and the Just Noticeable Difference (JND), either from a psychometric function or from a Generalized Linear Mixed Model (GLMM). Additionally, the package allows plotting the fitted models and the response data, simulating psychometric functions of different shapes, and simulating data sets. For a description of the use of GLMMs applied to psychophysical data, refer to Moscatelli et al. (2012).

r-multimode 1.5
Propagated dependencies: r-rootsolve@1.8.2.4 r-ks@1.15.1 r-diptest@0.77-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://doi.org/10.18637/jss.v097.i09
Licenses: GPL 3
Build system: r
Synopsis: Mode Testing and Exploring
Description:

Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2019 <DOI:10.1007/s11749-018-0611-5>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques <DOI:10.18637/jss.v097.i09>.

r-minired 1.0.1
Propagated dependencies: r-cpp11@0.5.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=minired
Licenses: GPL 3+
Build system: r
Synopsis: R Interface to 'Redatam' Library
Description:

This package is deprecated. Please use redatamx instead. Provides an API to work with Redatam (see <https://redatam.org>) databases in both formats: RXDB (new format) and DICX (old format) and running Redatam programs written in SPC language. It's a wrapper around Redatam core and provides functions to open/close a database (redatam_open()/redatam_close()), list entities and variables from the database (redatam_entities(), redatam_variables()) and execute a SPC program and gets the results as data frames (redatam_query(), redatam_run()).

r-malani 1.0
Propagated dependencies: r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=malani
Licenses: GPL 3
Build system: r
Synopsis: Machine Learning Assisted Network Inference
Description:

Find dark genes. These genes are often disregarded due to no detected mutation or differential expression, but are important in coordinating the functionality in cancer networks.

r-mcm 0.1.7
Propagated dependencies: r-survey@4.4-8 r-stringr@1.6.0 r-parameters@0.28.3 r-lme4@1.1-37 r-gee@4.13-29 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MCM
Licenses: GPL 2
Build system: r
Synopsis: Estimating and Testing Intergenerational Social Mobility Effect
Description:

Estimate and test inter-generational social mobility effect on an outcome with cross-sectional or longitudinal data.

r-mccmeiv 2.1
Propagated dependencies: r-survival@3.8-3 r-numderiv@2016.8-1.1 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=mccmeiv
Licenses: GPL 2
Build system: r
Synopsis: Analysis of Matched Case Control Data with a Mismeasured Exposure that is Accompanied by Instrumental Variables
Description:

Applying the methodology from Manuel et al. to estimate parameters using a matched case control data with a mismeasured exposure variable that is accompanied by instrumental variables (Submitted).

r-micefast 0.9.1
Propagated dependencies: 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/Polkas/miceFast
Licenses: GPL 2+
Build system: r
Synopsis: Fast Imputations Using 'Rcpp' and 'Armadillo'
Description:

Fast imputations under the object-oriented programming paradigm. Moreover there are offered a few functions built to work with popular R packages such as data.table or dplyr'. The biggest improvement in time performance can be achieved for a calculation where a grouping variable is used. A single evaluation of a quantitative model for the multiple imputations is another major enhancement. A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search.

r-mglmn 0.1.0
Propagated dependencies: r-snowfall@1.84-6.3 r-mvabund@4.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mattocci27/mglmn
Licenses: Expat
Build system: r
Synopsis: Model Averaging for Multivariate GLM with Null Models
Description:

This package provides tools for univariate and multivariate generalized linear models with model averaging and null model technique.

r-modelbpp 0.2.0
Propagated dependencies: r-pbapply@1.7-4 r-manymome@0.3.3 r-lavaan@0.6-20 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://sfcheung.github.io/modelbpp/
Licenses: GPL 3+
Build system: r
Synopsis: Model BIC Posterior Probability
Description:

Fits the neighboring models of a fitted structural equation model and assesses the model uncertainty of the fitted model based on BIC posterior probabilities (BPP), using the method presented in Wu, Cheung, and Leung (2020) <doi:10.1080/00273171.2019.1574546>. See Pesigan, Cheung, Wu, Chang, and Leung (2026) <doi:10.3758/s13428-025-02921-x> for an introduction to the package.

r-mapspain 1.0.0
Propagated dependencies: r-tibble@3.3.0 r-sf@1.0-23 r-rappdirs@0.3.3 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr2@1.2.1 r-giscor@1.0.1 r-countrycode@1.6.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://ropenspain.github.io/mapSpain/
Licenses: GPL 3
Build system: r
Synopsis: Administrative Boundaries of Spain
Description:

Administrative Boundaries of Spain at several levels (Autonomous Communities, Provinces, Municipalities) based on the GISCO Eurostat database <https://ec.europa.eu/eurostat/web/gisco> and CartoBase SIANE from Instituto Geografico Nacional <https://www.ign.es/>. It also provides a leaflet plugin and the ability of downloading and processing static tiles.

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-mixedbayes 0.2.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/kunfa/mixedBayes
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Longitudinal Regularized Quantile Mixed Model
Description:

With high-dimensional omics features, repeated measure ANOVA leads to longitudinal gene-environment interaction studies that have intra-cluster correlations, outlying observations and structured sparsity arising from the ANOVA design. In this package, we have developed robust sparse Bayesian mixed effect models tailored for the above studies (Fan et al. (2025) <doi:10.1093/jrsssc/qlaf027>). An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++'. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.

r-metabolicsurv 1.1.2
Propagated dependencies: r-tidyr@1.3.1 r-survminer@0.5.1 r-survival@3.8-3 r-superpc@1.12 r-rms@8.1-0 r-rdpack@2.6.4 r-pls@2.8-5 r-matrixstats@1.5.0 r-glmnet@4.1-10 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/OlajumokeEvangelina/MetabolicSurv
Licenses: GPL 3
Build system: r
Synopsis: Biomarker Validation Approach for Classification and Predicting Survival Using Metabolomics Signature
Description:

An approach to identifies metabolic biomarker signature for metabolic data by discovering predictive metabolite for predicting survival and classifying patients into risk groups. Classifiers are constructed as a linear combination of predictive/important metabolites, prognostic factors and treatment effects if necessary. Several methods were implemented to reduce the metabolomics matrix such as the principle component analysis of Wold Svante et al. (1987) <doi:10.1016/0169-7439(87)80084-9> , the LASSO method by Robert Tibshirani (1998) <doi:10.1002/(SICI)1097-0258(19970228)16:4%3C385::AID-SIM380%3E3.0.CO;2-3>, the elastic net approach by Hui Zou and Trevor Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>. Sensitivity analysis on the quantile used for the classification can also be accessed to check the deviation of the classification group based on the quantile specified. Large scale cross validation can be performed in order to investigate the mostly selected predictive metabolites and for internal validation. During the evaluation process, validation is accessed using the hazard ratios (HR) distribution of the test set and inference is mainly based on resampling and permutations technique.

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