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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-morsedr 0.1.2
Propagated dependencies: r-rjags@4-17 r-ggplot2@4.0.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=morseDR
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Inference of Binary, Count and Continuous Data in Toxicology
Description:

Advanced methods for a valuable quantitative environmental risk assessment using Bayesian inference of several type of toxicological data. binary (e.g., survival, mobility), count (e.g., reproduction) and continuous (e.g., growth as length, weight). Estimation procedures can be used without a deep knowledge of their underlying probabilistic model or inference methods. Rather, they were designed to behave as well as possible without requiring a user to provide values for some obscure parameters. That said, models can also be used as a first step to tailor new models for more specific situations.

r-molgenisarmadillo 2.9.3
Propagated dependencies: r-urltools@1.7.3.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlist@0.4.6.2 r-readr@2.1.6 r-purrr@1.2.0 r-molgenisauth@1.0.0 r-httr2@1.2.1 r-httr@1.4.7 r-dplyr@1.1.4 r-cli@3.6.5 r-base64enc@0.1-3 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/molgenis/molgenis-r-armadillo/
Licenses: LGPL 2.1+
Build system: r
Synopsis: Armadillo Client for the Armadillo Service
Description:

This package provides a set of functions to manage data shared on a MOLGENIS Armadillo server.

r-morepls 0.2.1
Propagated dependencies: r-rlang@1.1.6 r-pls@2.8-5 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-descriptio@1.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://framagit.org/nicolas-robette/morepls
Licenses: GPL 2+
Build system: r
Synopsis: Interpretation Tools for Partial Least Squares Regression
Description:

Various kinds of plots (observations, variables, correlations, weights, regression coefficients and Variable Importance in the Projection) and aids to interpretation (coefficients, Q2, correlations, redundancies) for partial least squares regressions computed with the pls package, following Tenenhaus (1998, ISBN:2-7108-0735-1).

r-madantextnetwork 0.1.0
Propagated dependencies: r-xlsx@0.6.5 r-visnetwork@2.1.4 r-udpipe@0.8.16 r-topicmodels@0.2-17 r-tm@0.7-16 r-tidytext@0.4.3 r-tidyr@1.3.1 r-textminer@3.0.6 r-stringr@1.6.0 r-stringi@1.8.7 r-stopwords@2.3 r-shinythemes@1.2.0 r-shiny@1.11.1 r-persianstemmer@1.0 r-ngram@3.2.3 r-lattice@0.22-7 r-igraph@2.2.1 r-hwordcloud@0.1.0 r-glue@1.8.0 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=MadanTextNetwork
Licenses: GPL 3
Build system: r
Synopsis: Persian Text Mining Tool for Co-Occurrence Network
Description:

This package provides an extension to MadanText for creating and analyzing co-occurrence networks in Persian text data. This package mainly makes use of the PersianStemmer (Safshekan, R., et al. (2019). <https://CRAN.R-project.org/package=PersianStemmer>), udpipe (Wijffels, J., et al. (2023). <https://CRAN.R-project.org/package=udpipe>), and shiny (Chang, W., et al. (2023). <https://CRAN.R-project.org/package=shiny>) packages.

r-msos 1.2.0
Propagated dependencies: r-tree@1.0-45 r-mclust@6.1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/coatless/msos
Licenses: Expat
Build system: r
Synopsis: Data Sets and Functions Used in Multivariate Statistics: Old School by John Marden
Description:

Multivariate Analysis methods and data sets used in John Marden's book Multivariate Statistics: Old School (2015) <ISBN:978-1456538835>. This also serves as a companion package for the STAT 571: Multivariate Analysis course offered by the Department of Statistics at the University of Illinois at Urbana-Champaign ('UIUC').

r-matchfeat 1.0
Propagated dependencies: r-foreach@1.5.2 r-clue@0.3-66
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=matchFeat
Licenses: GPL 2
Build system: r
Synopsis: One-to-One Feature Matching
Description:

Statistical methods to match feature vectors between multiple datasets in a one-to-one fashion. Given a fixed number of classes/distributions, for each unit, exactly one vector of each class is observed without label. The goal is to label the feature vectors using each label exactly once so to produce the best match across datasets, e.g. by minimizing the variability within classes. Statistical solutions based on empirical loss functions and probabilistic modeling are provided. The Gurobi software and its R interface package are required for one of the package functions (match.2x()) and can be obtained at <https://www.gurobi.com/> (free academic license). For more details, refer to Degras (2022) <doi:10.1080/10618600.2022.2074429> "Scalable feature matching for large data collections" and Bandelt, Maas, and Spieksma (2004) <doi:10.1057/palgrave.jors.2601723> "Local search heuristics for multi-index assignment problems with decomposable costs".

r-methscope 1.0.0
Dependencies: zlib@1.3.1
Propagated dependencies: r-xgboost@1.7.11.1 r-uwot@0.2.4 r-tidyr@1.3.1 r-stringr@1.6.0 r-nnls@1.6 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-fnn@1.1.4.1 r-dplyr@1.1.4 r-doparallel@1.0.17 r-data-table@1.17.8 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MethScope
Licenses: Expat
Build system: r
Synopsis: Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent Pattern Encoding
Description:

This package provides methods for analyzing DNA methylation data via Most Recurrent Methylation Patterns (MRMPs). Supports cell-type annotation, spatial deconvolution, unsupervised clustering, and cancer cell-of-origin inference. Includes C-backed summaries for YAME â .cg/.cmâ files (overlap counts, log2 odds ratios, beta/depth aggregation), an XGBoost classifier, NNLS deconvolution, and plotting utilities. Scales to large spatial and single-cell methylomes and is robust to extreme sparsity.

r-multimix 1.0-10
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/jmcurran/multimix
Licenses: GPL 2+
Build system: r
Synopsis: Fit Mixture Models Using the Expectation Maximisation (EM) Algorithm
Description:

This package provides a set of functions which use the Expectation Maximisation (EM) algorithm (Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, 39(1), 1--22) to take a finite mixture model approach to clustering. The package is designed to cluster multivariate data that have categorical and continuous variables and that possibly contain missing values. The method is described in Hunt, L. and Jorgensen, M. (1999) <doi:10.1111/1467-842X.00071> Australian & New Zealand Journal of Statistics 41(2), 153--171 and Hunt, L. and Jorgensen, M. (2003) <doi:10.1016/S0167-9473(02)00190-1> Mixture model clustering for mixed data with missing information, Computational Statistics & Data Analysis, 41(3-4), 429--440.

r-murphydiagram 0.12.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://sites.google.com/site/fk83research/code
Licenses: GPL 3
Build system: r
Synopsis: Murphy Diagrams for Forecast Comparisons
Description:

Data and code for the paper by Ehm, Gneiting, Jordan and Krueger ('Of Quantiles and Expectiles: Consistent Scoring Functions, Choquet Representations, and Forecast Rankings', JRSS-B, 2016 <DOI:10.1111/rssb.12154>).

r-multimediate 0.1.4
Propagated dependencies: r-timereg@2.0.7 r-rmutil@1.1.10 r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://samarafk.github.io/multimediate/
Licenses: GPL 3
Build system: r
Synopsis: Causal Mediation Analysis in Presence of Multiple Mediators Uncausally Related
Description:

Estimates key quantities in causal mediation analysis - including average causal mediation effects (indirect effects), average direct effects, total effects, and proportions mediated - in the presence of multiple uncausally related mediators. Methods are described by Jérolon et al., (2021) <doi:10.1515/ijb-2019-0088> and extended to accommodate survival outcomes as described by Domingo-Relloso et al., (2024) <doi:10.1101/2024.02.16.24302923>.

r-mcs 0.1.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MCS
Licenses: GPL 2
Build system: r
Synopsis: Model Confidence Set Procedure
Description:

Perform the model confidence set procedure of Hansen et al (2011) <doi:10.3982/ECTA5771>.

r-medscan 1.0.2
Propagated dependencies: r-qvalue@2.42.0 r-qqman@0.1.9 r-locfdr@1.1-8 r-hdmt@1.0.5 r-fdrtool@1.2.18
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/umich-cphds/medScan
Licenses: GPL 3
Build system: r
Synopsis: Large Scale Single Mediator Hypothesis Testing
Description:

This package provides a collection of methods for large scale single mediator hypothesis testing. The six included methods for testing the mediation effect are Sobel's test, Max P test, joint significance test under the composite null hypothesis, high dimensional mediation testing, divide-aggregate composite null test, and Sobel's test under the composite null hypothesis. Du et al (2023) <doi:10.1002/gepi.22510>.

r-msca 1.2.1
Propagated dependencies: r-rlang@1.1.6 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-fastkmedoids@1.2 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=MSCA
Licenses: GPL 3
Build system: r
Synopsis: Unsupervised Clustering of Multiple Censored Time-to-Event Endpoints
Description:

This package provides basic tools and wrapper functions for computing clusters of instances described by multiple time-to-event censored endpoints. From long-format datasets, where one instance is described by one or more dated records, the main function, `make_state_matrices()`, creates state matrices. Based on these matrices, optimised procedures using the Jaccard distance between instances enable the construction of longitudinal typologies. The package is under active development, with additional tools for graphical representation of typologies planned. For methodological details, see our accompanying paper: `Delord M, Douiri A (2025) <doi:10.1186/s12874-025-02476-7>`.

r-mmcmcbayes 0.2.0
Propagated dependencies: r-mcmcpack@1.7-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/zyang1919/mmcmcBayes
Licenses: GPL 3
Build system: r
Synopsis: Multistage MCMC Method for Detecting DMRs
Description:

This package implements differential methylation region (DMR) detection using a multistage Markov chain Monte Carlo (MCMC) algorithm based on the alpha-skew generalized normal (ASGN) distribution. Version 0.2.0 removes the Anderson-Darling test stage, improves computational efficiency of the core ASGN and multistage MCMC routines, and adds convenience functions for summarizing and visualizing detected DMRs. The methodology is based on Yang (2025) <https://www.proquest.com/docview/3218878972>.

r-matlab 1.0.4.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=matlab
Licenses: Artistic License 2.0
Build system: r
Synopsis: 'MATLAB' Emulation Package
Description:

Emulate MATLAB code using R'.

r-mlf 1.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://mlf-project.us/
Licenses: GPL 2
Build system: r
Synopsis: Machine Learning Foundations
Description:

Offers a gentle introduction to machine learning concepts for practitioners with a statistical pedigree: decomposition of model error (bias-variance trade-off), nonlinear correlations, information theory and functional permutation/bootstrap simulations. Székely GJ, Rizzo ML, Bakirov NK. (2007). <doi:10.1214/009053607000000505>. Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ, Lander ES, Mitzenmacher M, Sabeti PC. (2011). <doi:10.1126/science.1205438>.

r-mcpmod 1.0-10.1
Propagated dependencies: r-mvtnorm@1.3-3 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MCPMod
Licenses: GPL 3
Build system: r
Synopsis: Design and Analysis of Dose-Finding Studies
Description:

This package implements a methodology for the design and analysis of dose-response studies that combines aspects of multiple comparison procedures and modeling approaches (Bretz, Pinheiro and Branson, 2005, Biometrics 61, 738-748, <doi: 10.1111/j.1541-0420.2005.00344.x>). The package provides tools for the analysis of dose finding trials as well as a variety of tools necessary to plan a trial to be conducted with the MCP-Mod methodology. Please note: The MCPMod package will not be further developed, all future development of the MCP-Mod methodology will be done in the DoseFinding R-package.

r-mkdescr 0.9
Propagated dependencies: r-scales@1.4.0 r-rlang@1.1.6 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/stamats/MKdescr
Licenses: LGPL 3
Build system: r
Synopsis: Descriptive Statistics
Description:

Computation of standardized interquartile range (IQR), Huber-type skipped mean (Hampel (1985), <doi:10.2307/1268758>), robust coefficient of variation (CV) (Arachchige et al. (2019), <doi:10.48550/arXiv.1907.01110>), robust signal to noise ratio (SNR), z-score, standardized mean difference (SMD), as well as functions that support graphical visualization such as boxplots based on quartiles (not hinges), negative logarithms and generalized logarithms for ggplot2 (Wickham (2016), ISBN:978-3-319-24277-4).

r-mazamaspatialutils 0.8.7
Propagated dependencies: r-stringr@1.6.0 r-sf@1.0-23 r-rmapshaper@0.5.0 r-rlang@1.1.6 r-mazamacoreutils@0.6.0 r-magrittr@2.0.4 r-dplyr@1.1.4 r-countrycode@1.6.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/MazamaScience/MazamaSpatialUtils
Licenses: GPL 2
Build system: r
Synopsis: Spatial Data Download and Utility Functions
Description:

This package provides a suite of conversion functions to create internally standardized spatial polygons data frames. Utility functions use these data sets to return values such as country, state, time zone, watershed, etc. associated with a set of longitude/latitude pairs. (They also make cool maps.).

r-mapboxer 0.4.0
Propagated dependencies: r-yaml@2.3.10 r-purrr@1.2.0 r-magrittr@2.0.4 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1 r-geojsonsf@2.0.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/crazycapivara/mapboxer
Licenses: Expat
Build system: r
Synopsis: An R Interface to 'Mapbox GL JS'
Description:

Makes Mapbox GL JS <https://docs.mapbox.com/mapbox-gl-js/api/>, an open source JavaScript library that uses WebGL to render interactive maps, available within R via the htmlwidgets package. Visualizations can be used from the R console, in R Markdown documents and in Shiny apps.

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
Build system: r
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-multiapply 2.1.5
Propagated dependencies: r-plyr@1.8.9 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://earth.bsc.es/gitlab/ces/multiApply
Licenses: GPL 3
Build system: r
Synopsis: Apply Functions to Multiple Multidimensional Arrays or Vectors
Description:

The base apply function and its variants, as well as the related functions in the plyr package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The multiApply package extends this paradigm with its only function, Apply, which efficiently applies functions taking one or a list of multiple unidimensional or multidimensional arrays (or combinations thereof) as input. The input arrays can have different numbers of dimensions as well as different dimension lengths, and the applied function can return one or a list of unidimensional or multidimensional arrays as output. This saves development time by preventing the R user from writing often error-prone and memory-inefficient loops dealing with multiple complex arrays. Also, a remarkable feature of Apply is the transparent use of multi-core through its parameter ncores'. In contrast to the base apply function, this package suggests the use of target dimensions as opposite to the margins for specifying the dimensions relevant to the function to be applied.

r-mev 2.1
Propagated dependencies: r-rsolnp@2.0.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-nleqslv@3.3.5 r-alabama@2023.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://lbelzile.github.io/mev/
Licenses: GPL 3
Build system: r
Synopsis: Modelling of Extreme Values
Description:

Various tools for the analysis of univariate, multivariate and functional extremes. Exact simulation from max-stable processes (Dombry, Engelke and Oesting, 2016, <doi:10.1093/biomet/asw008>, R-Pareto processes for various parametric models, including Brown-Resnick (Wadsworth and Tawn, 2014, <doi:10.1093/biomet/ast042>) and Extremal Student (Thibaud and Opitz, 2015, <doi:10.1093/biomet/asv045>). Threshold selection methods, including Wadsworth (2016) <doi:10.1080/00401706.2014.998345>, and Northrop and Coleman (2014) <doi:10.1007/s10687-014-0183-z>. Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., Coles (2001) <doi:10.1007/978-1-4471-3675-0>.

r-microdatoses 0.8.15
Propagated dependencies: r-readr@2.1.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.datanalytics.com/2012/08/06/un-paseo-por-el-paquete-microdatoses-y-la-epa-de-nuevo/
Licenses: GPL 3
Build system: r
Synopsis: Utilities for Official Spanish Microdata
Description:

This package provides utilities for reading and processing microdata from Spanish official statistics with R.

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Total results: 68658