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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-mapgam 1.3-1
Propagated dependencies: r-survival@3.8-3 r-sp@2.2-0 r-sf@1.0-23 r-pbsmapping@2.74.1 r-gam@1.22-6 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MapGAM
Licenses: GPL 3
Build system: r
Synopsis: Mapping Smoothed Effect Estimates from Individual-Level Data
Description:

This package contains functions for mapping odds ratios, hazard ratios, or other effect estimates using individual-level data such as case-control study data, using generalized additive models (GAMs) or Cox models for smoothing with a two-dimensional predictor (e.g., geolocation or exposure to chemical mixtures) while adjusting linearly for confounding variables, using methods described by Kelsall and Diggle (1998), Webster at al. (2006), and Bai et al. (2020). Includes convenient functions for mapping point estimates and confidence intervals, efficient control sampling, and permutation tests for the null hypothesis that the two-dimensional predictor is not associated with the outcome variable (adjusting for confounders).

r-micecon 0.6-20
Propagated dependencies: r-plm@2.6-7 r-misctools@0.6-28
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://www.micEcon.org
Licenses: GPL 2+
Build system: r
Synopsis: Microeconomic Analysis and Modelling
Description:

Various tools for microeconomic analysis and microeconomic modelling, e.g. estimating quadratic, Cobb-Douglas and Translog functions, calculating partial derivatives and elasticities of these functions, and calculating Hessian matrices, checking curvature and preparing restrictions for imposing monotonicity of Translog functions.

r-mittagleffler 0.4.1
Propagated dependencies: r-stabledist@0.7-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://strakaps.github.io/MittagLeffleR/
Licenses: GPL 2+
Build system: r
Synopsis: Mittag-Leffler Family of Distributions
Description:

This package implements the Mittag-Leffler function, distribution, random variate generation, and estimation. Based on the Laplace-Inversion algorithm by Garrappa, R. (2015) <doi:10.1137/140971191>.

r-medicaldata 0.2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://higgi13425.github.io/medicaldata/
Licenses: Expat
Build system: r
Synopsis: Data Package for Medical Datasets
Description:

This package provides access to well-documented medical datasets for teaching. Featuring several from the Teaching of Statistics in the Health Sciences website <https://www.causeweb.org/tshs/category/dataset/>, a few reconstructed datasets of historical significance in medical research, some reformatted and extended from existing R packages, and some data donations.

r-mrhawkes 1.0
Propagated dependencies: r-ihsep@0.3.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MRHawkes
Licenses: GPL 2+
Build system: r
Synopsis: Multivariate Renewal Hawkes Process
Description:

Simulate a (bivariate) multivariate renewal Hawkes (MRHawkes) self-exciting process, with given immigrant hazard rate functions and offspring density function. Calculate the likelihood of a MRHawkes process with given hazard rate functions and offspring density function for an (increasing) sequence of event times. Calculate the Rosenblatt residuals of the event times. Predict future event times based on observed event times up to a given time. For details see Stindl and Chen (2018) <doi:10.1016/j.csda.2018.01.021>.

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-matchgate 0.0.10
Propagated dependencies: r-locpol@0.9.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MatchGATE
Licenses: GPL 3
Build system: r
Synopsis: Estimate Group Average Treatment Effects with Matching
Description:

Two novel matching-based methods for estimating group average treatment effects (GATEs). The match_y1y0() and match_y1y0_bc() functions are used for imputing the potential outcomes based on matching and bias-corrected matching techniques, respectively. The EstGATE() function is employed to estimate the GATE after imputing the potential outcomes.

r-mlsjunkgen 0.1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://stevemyles.site/mlsjunkgen/
Licenses: Expat
Build system: r
Synopsis: Use the MLS Junk Generator Algorithm to Generate a Stream of Pseudo-Random Numbers
Description:

Generate a stream of pseudo-random numbers generated using the MLS Junk Generator algorithm. Functions exist to generate single pseudo-random numbers as well as a vector, data frame, or matrix of pseudo-random numbers.

r-multiocc 0.2.3
Propagated dependencies: r-truncnorm@1.0-9 r-tmvtnorm@1.7 r-mass@7.3-65 r-interp@1.1-6 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=multiocc
Licenses: GPL 2
Build system: r
Synopsis: Fits Multivariate Spatio-Temporal Occupancy Model
Description:

Spatio-temporal multivariate occupancy models can handle multiple species in occupancy models. This method for fitting such models is described in Hepler and Erhardt (2021) "A spatiotemporal model for multivariate occupancy data".

r-mdag 1.2.3
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pcalg@2.7-12 r-nnet@7.3-20 r-mgm@1.2-15 r-logistf@1.26.1 r-bnlearn@5.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mDAG
Licenses: GPL 2+
Build system: r
Synopsis: Inferring Causal Network from Mixed Observational Data Using a Directed Acyclic Graph
Description:

Learning a mixed directed acyclic graph based on both continuous and categorical data.

r-matchthem 1.2.1
Propagated dependencies: r-weightit@1.5.1 r-survey@4.4-8 r-rlang@1.1.6 r-mice@3.18.0 r-matchit@4.7.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/FarhadPishgar/MatchThem
Licenses: GPL 2+
Build system: r
Synopsis: Matching and Weighting Multiply Imputed Datasets
Description:

This package provides essential tools for the pre-processing techniques of matching and weighting multiply imputed datasets. The package includes functions for matching within and across multiply imputed datasets using various methods, estimating weights for units in the imputed datasets using multiple weighting methods, calculating causal effect estimates in each matched or weighted dataset using parametric or non-parametric statistical models, and pooling the resulting estimates according to Rubin's rules (please see <https://journal.r-project.org/archive/2021/RJ-2021-073/> for more details).

r-mhtrajectoryr 1.0.1
Propagated dependencies: r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MHTrajectoryR
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Model Selection in Logistic Regression for the Detection of Adverse Drug Reactions
Description:

Spontaneous adverse event reports have a high potential for detecting adverse drug reactions. However, due to their dimension, the analysis of such databases requires statistical methods. We propose to use a logistic regression whose sparsity is viewed as a model selection challenge. Since the model space is huge, a Metropolis-Hastings algorithm carries out the model selection by maximizing the BIC criterion.

r-msda 1.0.4
Propagated dependencies: 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://github.com/archer-yang-lab/msda
Licenses: GPL 2
Build system: r
Synopsis: Multi-Class Sparse Discriminant Analysis
Description:

Efficient procedures for computing a new Multi-Class Sparse Discriminant Analysis method that estimates all discriminant directions simultaneously. It is an implementation of the work proposed by Mai, Q., Yang, Y., and Zou, H. (2019) <doi:10.5705/ss.202016.0117>.

r-multideggs 1.1.3
Propagated dependencies: r-visnetwork@2.1.4 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-sfsmisc@1.1-23 r-rmarkdown@2.30 r-pbmcapply@1.5.1 r-pbapply@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-knitr@1.50 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/elisabettasciacca/multiDEGGs/
Licenses: GPL 3
Build system: r
Synopsis: Multi-Omic Differentially Expressed Gene-Gene Pairs
Description:

This package performs multi-omic differential network analysis by revealing differential interactions between molecular entities (genes, proteins, transcription factors, or other biomolecules) across the omic datasets provided. For each omic dataset, a differential network is constructed where links represent statistically significant differential interactions between entities. These networks are then integrated into a comprehensive visualization using distinct colors to distinguish interactions from different omic layers. This unified display allows interactive exploration of cross-omic patterns, such as differential interactions present at both transcript and protein levels. For each link, users can access differential statistical significance metrics (p values or adjusted p values, calculated via robust or traditional linear regression with interaction term) and differential regression plots. The methods implemented in this package are described in Sciacca et al. (2023) <doi:10.1093/bioinformatics/btad192>.

r-modelsse 0.1-3
Propagated dependencies: r-delaporte@8.4.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=modelSSE
Licenses: GPL 3
Build system: r
Synopsis: Modelling Infectious Disease Superspreading from Contact Tracing Data
Description:

Comprehensive analytical tools are provided to characterize infectious disease superspreading from contact tracing surveillance data. The underlying theoretical frameworks of this toolkit include branching process with transmission heterogeneity (Lloyd-Smith et al. (2005) <doi:10.1038/nature04153>), case cluster size distribution (Nishiura et al. (2012) <doi:10.1016/j.jtbi.2011.10.039>, Blumberg et al. (2014) <doi:10.1371/journal.ppat.1004452>, and Kucharski and Althaus (2015) <doi:10.2807/1560-7917.ES2015.20.25.21167>), and decomposition of reproduction number (Zhao et al. (2022) <doi:10.1371/journal.pcbi.1010281>).

r-meanr 0.1-6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/wrathematics/meanr
Licenses: FSDG-compatible
Build system: r
Synopsis: Sentiment Analysis Scorer
Description:

Sentiment analysis is a popular technique in text mining that attempts to determine the emotional state of some text. We provide a new implementation of a common method for computing sentiment, whereby words are scored as positive or negative according to a dictionary lookup. Then the sum of those scores is returned for the document. We use the Hu and Liu sentiment dictionary ('Hu and Liu', 2004) <doi:10.1145/1014052.1014073> for determining sentiment. The scoring function is vectorized by document, and scores for multiple documents are computed in parallel via OpenMP'.

r-multiobjmatch 1.0.0
Propagated dependencies: r-rlemon@0.2.1 r-rlang@1.1.6 r-rcurl@1.98-1.17 r-rcbalance@1.8.8 r-plyr@1.8.9 r-optmatch@0.10.8 r-matchmulti@1.1.14 r-mass@7.3-65 r-gtools@3.9.5 r-ggplot2@4.0.1 r-fields@17.1 r-dplyr@1.1.4 r-cobalt@4.6.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiObjMatch
Licenses: Expat
Build system: r
Synopsis: Multi-Objective Matching Algorithm
Description:

Matching algorithm based on network-flow structure. Users are able to modify the emphasis on three different optimization goals: two different distance measures and the number of treated units left unmatched. The method is proposed by Pimentel and Kelz (2019) <doi:10.1080/01621459.2020.1720693>. The rrelaxiv package, which provides an alternative solver for the underlying network flow problems, carries an academic license and is not available on CRAN, but may be downloaded from Github at <https://github.com/josherrickson/rrelaxiv/>.

r-metarep 1.2.1
Propagated dependencies: r-meta@8.2-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/IJaljuli/metarep
Licenses: GPL 2+
Build system: r
Synopsis: Replicability-Analysis Tools for Meta-Analysis
Description:

User-friendly package for reporting replicability-analysis methods, affixed to meta-analyses summary. The replicability-analysis output provides an assessment of the investigated intervention, where it offers quantification of effect replicability and assessment of the consistency of findings. - Replicability-analysis for fixed-effects and random-effect meta analysis: - r(u)-value; - lower bounds on the number of studies with replicated positive and\or negative effect; - Allows detecting inconsistency of signals; - forest plots with the summary of replicability analysis results; - Allows Replicability-analysis with or without the common-effect assumption.

r-mixdir 0.3.0
Propagated dependencies: r-rcpp@1.1.0 r-extradistr@1.10.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/const-ae/mixdir
Licenses: GPL 3
Build system: r
Synopsis: Cluster High Dimensional Categorical Datasets
Description:

Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet (Process) mixture of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used to reduce the dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically infer an appropriate number of latent classes or find k classes, as defined by the user. The model is based on a paper by Dunson and Xing (2009) <doi:10.1198/jasa.2009.tm08439>, but implements a scalable variational inference algorithm so that it is applicable to large datasets. It is described and tested in the accompanying paper by Ahlmann-Eltze and Yau (2018) <doi:10.1109/DSAA.2018.00068>.

r-mauricer 2.5.4
Propagated dependencies: r-stringr@1.6.0 r-beastier@2.5.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://docs.ropensci.org/mauricer/https://github.com/ropensci/mauricer
Licenses: GPL 3
Build system: r
Synopsis: Work with 'BEAST2' Packages
Description:

BEAST2 (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. BEAST2 is commonly accompanied by BEAUti 2 (<https://www.beast2.org>), which, among others, allows one to install BEAST2 package. This package allows to work with BEAST2 packages from R'.

r-mort 0.0.1
Propagated dependencies: r-rlang@1.1.6 r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/rosieluain/mort
Licenses: GPL 3+
Build system: r
Synopsis: Identifying Potential Mortalities and Expelled Tags in Aquatic Acoustic Telemetry Arrays
Description:

This package provides a toolkit for identifying potential mortalities and expelled tags in aquatic acoustic telemetry arrays. Designed for arrays with non-overlapping receivers.

r-mram 1.0.0
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
Build system: r
Synopsis: Multivariate Regression Association Measure
Description:

Implementations of an estimator for the multivariate regression association measure (MRAM) proposed in Shih and Chen (2026) <doi:10.1016/j.csda.2025.108288> 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 (2026) <doi:10.1016/j.csda.2025.108288>.

r-metapack 0.3
Propagated dependencies: r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-gridextra@2.3 r-ggplot2@4.0.1 r-formula@1.2-5 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://events.stat.uconn.edu/metapack/
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Meta-Analysis and Network Meta-Analysis
Description:

This package contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Hui Yao, Sungduk Kim, Ming-Hui Chen, Joseph G. Ibrahim, Arvind K. Shah, and Jianxin Lin (2015) <doi:10.1080/01621459.2015.1006065> and Hao Li, Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. Shah, Jianxin Lin (2021) <doi:10.1002/sim.8983>. For maximal computational efficiency, the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. This software has been developed under the auspices of the National Institutes of Health and Merck & Co., Inc., Kenilworth, NJ, USA.

r-mtscr 2.0.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-lifecycle@1.0.4 r-glue@1.8.0 r-glmmtmb@1.1.13 r-dplyr@1.1.4 r-cli@3.6.5 r-broom-mixed@0.2.9.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/jakub-jedrusiak/mtscr
Licenses: Expat
Build system: r
Synopsis: Multidimensional Top Scoring for Creativity Research
Description:

Implementation of Multidimensional Top Scoring method for creativity assessment proposed in Boris Forthmann, Maciej Karwowski, Roger E. Beaty (2023) <doi:10.1037/aca0000571>.

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