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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-mfcurve 1.0.2
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-rlang@1.1.6 r-plotly@4.11.0 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/XAM12/mfcurve_R
Licenses: GPL 3+
Build system: r
Synopsis: Multi-Factor Curve Analysis for Grouped Data in 'R'
Description:

This package implements multi-factor curve analysis for grouped data in R', replicating and extending the functionality of the the Stata ado mfcurve (Krähmer, 2023) <https://ideas.repec.org/c/boc/bocode/s459224.html>. Related to the idea of specification curve analysis (Simonsohn, Simmons, and Nelson, 2020) <doi:10.1038/s41562-020-0912-z>. Includes data preprocessing, statistical testing, and visualization of results with confidence intervals.

r-mappoly 0.4.2
Dependencies: zlib@1.3.1
Propagated dependencies: r-zoo@1.8-14 r-vcfr@1.15.0 r-smacof@2.1-7 r-rstudioapi@0.17.1 r-reshape2@1.4.5 r-rcurl@1.98-1.17 r-rcppparallel@5.1.11-1 r-rcpp@1.1.0 r-princurve@2.1.6 r-plotly@4.11.0 r-magrittr@2.0.4 r-ggsci@4.1.0 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-fields@17.1 r-dplyr@1.1.4 r-dendextend@1.19.1 r-crayon@1.5.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mmollina/MAPpoly
Licenses: GPL 3
Build system: r
Synopsis: Genetic Linkage Maps in Autopolyploids
Description:

Constructs genetic linkage maps in autopolyploid full-sib populations. Uses pairwise recombination fraction estimation as the first source of information to sequentially position allelic variants in specific homologous chromosomes. For situations where pairwise analysis has limited power, the algorithm relies on the multilocus likelihood obtained through a hidden Markov model (HMM). Methods are described in Mollinari and Garcia (2019) <doi:10.1534/g3.119.400378> and Mollinari et al. (2020) <doi:10.1534/g3.119.400620>.

r-mtrank 0.2-0
Propagated dependencies: r-plackettluce@0.4.4 r-netmeta@3.3-1 r-meta@8.2-1 r-magrittr@2.0.4 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/TEvrenoglou/mtrank
Licenses: GPL 2+
Build system: r
Synopsis: Ranking using Probabilistic Models and Treatment Choice Criteria
Description:

Estimation of treatment hierarchies in network meta-analysis using a novel frequentist approach based on treatment choice criteria (TCC) and probabilistic ranking models, as described by Evrenoglou et al. (2024) <DOI:10.48550/arXiv.2406.10612>. The TCC are defined using a rule based on the smallest worthwhile difference (SWD). Using the defined TCC, the NMA estimates (i.e., treatment effects and standard errors) are first transformed into treatment preferences, indicating either a treatment preference (e.g., treatment A > treatment B) or a tie (treatment A = treatment B). These treatment preferences are then synthesized using a probabilistic ranking model, which estimates the latent ability parameter of each treatment and produces the final treatment hierarchy. This parameter represents each treatments ability to outperform all the other competing treatments in the network. Here the terms ability to outperform indicates the propensity of each treatment to yield clinically important and beneficial effects when compared to all the other treatments in the network. Consequently, larger ability estimates indicate higher positions in the ranking list.

r-mplot 1.0.6
Propagated dependencies: r-tidyr@1.3.1 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-scales@1.4.0 r-reshape2@1.4.5 r-plyr@1.8.9 r-magrittr@2.0.4 r-leaps@3.2 r-googlevis@0.7.3 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-dorng@1.8.6.2 r-doparallel@1.0.17 r-bestglm@0.37.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://garthtarr.github.io/mplot/
Licenses: GPL 2+
Build system: r
Synopsis: Graphical Model Stability and Variable Selection Procedures
Description:

Model stability and variable inclusion plots [Mueller and Welsh (2010, <doi:10.1111/j.1751-5823.2010.00108.x>); Murray, Heritier and Mueller (2013, <doi:10.1002/sim.5855>)] as well as the adaptive fence [Jiang et al. (2008, <doi:10.1214/07-AOS517>); Jiang et al. (2009, <doi:10.1016/j.spl.2008.10.014>)] for linear and generalised linear models.

r-multicastr 2.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://multicast.aspra.uni-bamberg.de/
Licenses: FSDG-compatible
Build system: r
Synopsis: Companion to the Multi-CAST Collection
Description:

This package provides a basic interface for accessing annotation data from the Multi-CAST collection, a database of spoken natural language texts edited by Geoffrey Haig and Stefan Schnell. The collection draws from a diverse set of languages and has been annotated across multiple levels. Annotation data is downloaded on request from the servers of the University of Bamberg. See the Multi-CAST website <https://multicast.aspra.uni-bamberg.de/> for more information and a list of related publications.

r-melt 1.11.4
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-dqrng@0.4.1 r-checkmate@2.3.3 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://docs.ropensci.org/melt/
Licenses: GPL 2+
Build system: r
Synopsis: Multiple Empirical Likelihood Tests
Description:

This package performs multiple empirical likelihood tests. It offers an easy-to-use interface and flexibility in specifying hypotheses and calibration methods, extending the framework to simultaneous inferences. The core computational routines are implemented using the Eigen C++ library and RcppEigen interface, with OpenMP for parallel computation. Details of the testing procedures are provided in Kim, MacEachern, and Peruggia (2023) <doi:10.1080/10485252.2023.2206919>. A companion paper by Kim, MacEachern, and Peruggia (2024) <doi:10.18637/jss.v108.i05> is available for further information. This work was supported by the U.S. National Science Foundation under Grants No. SES-1921523 and DMS-2015552.

r-msml 1.0.0.1
Propagated dependencies: r-r2roc@1.0.1 r-r2redux@1.0.18
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mommy003/MSML
Licenses: GPL 3+
Build system: r
Synopsis: Model Selection Based on Machine Learning (ML)
Description:

Model evaluation based on a modified version of the recursive feature elimination algorithm. This package is designed to determine the optimal model(s) by leveraging all available features.

r-msoutcomes 0.2.1
Propagated dependencies: 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=MSoutcomes
Licenses: Expat
Build system: r
Synopsis: CORe Multiple Sclerosis Outcomes Toolkit
Description:

Enable operationalized evaluation of disease outcomes in multiple sclerosis. â MSoutcomesâ requires longitudinally recorded clinical data structured in long format. The package is based on the research developed at Clinical Outcomes Research unit (CORe), University of Melbourne and Neuroimmunology Centre, Royal Melbourne Hospital. Kalincik et al. (2015) <doi:10.1093/brain/awv258>. Lorscheider et al. (2016) <doi:10.1093/brain/aww173>. Sharmin et al. (2022) <doi:10.1111/ene.15406>. Dzau et al. (2023) <doi:10.1136/jnnp-2023-331748>.

r-mlmm-gwas 1.0.6
Propagated dependencies: r-sommer@4.4.4 r-multcompview@0.1-10 r-multcomp@1.4-29 r-matrix@1.7-4 r-coxme@2.2-22
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mlmm.gwas
Licenses: GPL 3
Build system: r
Synopsis: Pipeline for GWAS Using MLMM
Description:

Pipeline for Genome-Wide Association Study using Multi-Locus Mixed Model from Segura V, Vilhjálmsson BJ et al. (2012) <doi:10.1038/ng.2314>. The pipeline include detection of associated SNPs with MLMM, model selection by lowest eBIC and p-value threshold, estimation of the effects of the SNPs in the selected model and graphical functions.

r-mixtree 0.0.1
Propagated dependencies: r-vegan@2.7-2 r-treespace@1.1.4.4 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cygei.github.io/mixtree/
Licenses: Expat
Build system: r
Synopsis: Statistical Framework for Comparing Sets of Trees
Description:

Statistical framework for comparing sets of trees using hypothesis testing methods. Designed for transmission trees, phylogenetic trees, and directed acyclic graphs (DAGs), the package implements chi-squared tests to compare edge frequencies between sets and PERMANOVA to analyse topological dissimilarities with customisable distance metrics, following Anderson (2001) <doi:10.1111/j.1442-9993.2001.01070.pp.x>.

r-mvhtests 1.1
Propagated dependencies: r-rfast2@0.1.5.6 r-rfast@2.1.5.2 r-foreach@1.5.2 r-emplik@1.3-2 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=mvhtests
Licenses: GPL 2+
Build system: r
Synopsis: Multivariate Hypothesis Tests
Description:

Hypothesis tests for multivariate data. Tests for one and two mean vectors, multivariate analysis of variance, tests for one, two or more covariance matrices. References include: Mardia K.V., Kent J.T. and Bibby J.M. (1979). Multivariate Analysis. ISBN: 978-0124712522. London: Academic Press.

r-merror 3.0
Propagated dependencies: r-openmx@2.22.10
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=merror
Licenses: GPL 2+
Build system: r
Synopsis: Accuracy and Precision of Measurements
Description:

N>=3 methods are used to measure each of n items. The data are used to estimate simultaneously systematic error (bias) and random error (imprecision). Observed measurements for each method or device are assumed to be linear functions of the unknown true values and the errors are assumed normally distributed. Pairwise calibration curves and plots can be easily generated. Unlike the ncb.od function, the omx function builds a one-factor measurement error model using OpenMx and allows missing values, uses full information maximum likelihood to estimate parameters, and provides both likelihood-based and bootstrapped confidence intervals for all parameters, in addition to Wald-type intervals.

r-msgps 1.3.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://keihirose.com/
Licenses: GPL 2+
Build system: r
Synopsis: Degrees of Freedom of Elastic Net, Adaptive Lasso and Generalized Elastic Net
Description:

Computes the degrees of freedom of the lasso, elastic net, generalized elastic net and adaptive lasso based on the generalized path seeking algorithm. The optimal model can be selected by model selection criteria including Mallows Cp, bias-corrected AIC (AICc), generalized cross validation (GCV) and BIC.

r-memoir 1.3-1
Dependencies: pandoc@2.19.2
Propagated dependencies: r-usethis@3.2.1 r-rmdformats@1.0.4 r-rmarkdown@2.30 r-distill@1.6 r-bookdown@0.45
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://ericmarcon.github.io/memoiR/
Licenses: GPL 3+
Build system: r
Synopsis: R Markdown and Bookdown Templates to Publish Documents
Description:

Producing high-quality documents suitable for publication directly from R is made possible by the R Markdown ecosystem. memoiR makes it easy. It provides templates to knit memoirs, articles and slideshows with helpers to publish the documents on GitHub Pages and activate continuous integration.

r-multivarmi 1.0
Propagated dependencies: r-poisnonnor@1.6.3 r-norm@1.0-11.1 r-moments@0.14.1 r-matrix@1.7-4 r-corrtoolbox@1.6.4 r-corpcor@1.6.10 r-binordnonnor@1.5.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiVarMI
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Multiple Imputation for Multivariate Data
Description:

Fully parametric Bayesian multiple imputation framework for massive multivariate data of different variable types as seen in Demirtas, H. (2017) <doi:10.1007/978-981-10-3307-0_8>.

r-msg 0.9
Propagated dependencies: r-rcolorbrewer@1.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/yihui/MSG
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Data and Functions for the Book Modern Statistical Graphics
Description:

This package provides a companion to the Chinese book ``Modern Statistical Graphics''.

r-mailmerge 0.2.5
Propagated dependencies: r-shiny@1.11.1 r-rstudioapi@0.17.1 r-rmarkdown@2.30 r-purrr@1.2.0 r-miniui@0.1.2 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-googledrive@2.1.2 r-gmailr@3.0.0 r-glue@1.8.0 r-fs@1.6.6 r-commonmark@2.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://andrie.github.io/mailmerge/
Licenses: Expat
Build system: r
Synopsis: Mail Merge Using R Markdown Documents and 'gmailr'
Description:

Perform a mail merge (mass email) using the message defined in markdown, the recipients in a csv file, and gmail as the mailing engine. With this package you can parse markdown documents as the body of email, and the yaml header to specify the subject line of the email. Any braces in the email will be encoded with glue::glue()'. You can preview the email in the RStudio viewer pane, and send (draft) email using gmailr'.

r-mimer 1.0.5
Propagated dependencies: r-tidyr@1.3.1 r-testthat@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-reshape2@1.4.5 r-fuzzyjoin@0.1.6.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-amr@3.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MIMER
Licenses: GPL 3+
Build system: r
Synopsis: Data Wrangling for Antimicrobial Resistance Studies
Description:

Designed for analyzing the Medical Information Mart for Intensive Care(MIMIC) dataset, a repository of freely accessible electronic health records. MIMER(MIMIC-enabled Research) package, offers a suite of data wrangling functions tailored specifically for preparing the dataset for research purposes, particularly in antimicrobial resistance(AMR) studies. It simplifies complex data manipulation tasks, allowing researchers to focus on their primary inquiries without being bogged down by wrangling complexities.

r-makefiler 1.1.0
Propagated dependencies: r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://gitlab.com/fvafrcu/MakefileR
Licenses: GPL 3
Build system: r
Synopsis: Create 'Makefiles' Using R
Description:

This package provides a user-friendly interface for the construction of Makefiles'.

r-midas2 1.1.0
Propagated dependencies: r-r2jags@0.8-9 r-mcmcpack@1.7-1 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=midas2
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Platform Design with Subgroup Efficacy Exploration(MIDAS-2)
Description:

The rapid screening of effective and optimal therapies from large numbers of candidate combinations, as well as exploring subgroup efficacy, remains challenging, which necessitates innovative, integrated, and efficient trial designs(Yuan, Y., et al. (2016) <doi:10.1002/sim.6971>). MIDAS-2 package enables quick and continuous screening of promising combination strategies and exploration of their subgroup effects within a unified platform design framework. We used a regression model to characterize the efficacy pattern in subgroups. Information borrowing was applied through Bayesian hierarchical model to improve trial efficiency considering the limited sample size in subgroups(Cunanan, K. M., et al. (2019) <doi:10.1177/1740774518812779>). MIDAS-2 provides an adaptive drug screening and subgroup exploring framework to accelerate immunotherapy development in an efficient, accurate, and integrated fashion(Wathen, J. K., & Thall, P. F. (2017) <doi: 10.1177/1740774517692302>).

r-mcpan 1.1-21
Propagated dependencies: r-plyr@1.8.9 r-mvtnorm@1.3-3 r-multcomp@1.4-29 r-mcmcpack@1.7-1 r-magic@1.6-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MCPAN
Licenses: GPL 2
Build system: r
Synopsis: Multiple Comparisons Using Normal Approximation
Description:

Multiple contrast tests and simultaneous confidence intervals based on normal approximation. With implementations for binomial proportions in a 2xk setting (risk difference and odds ratio), poly-3-adjusted tumour rates, biodiversity indices (multinomial data) and expected values under lognormal assumption. Approximative power calculation for multiple contrast tests of binomial and Gaussian data.

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-maicchecks 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-quadprog@1.5-8 r-lpsolve@5.6.23 r-ggplot2@4.0.1 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=maicChecks
Licenses: GPL 3+
Build system: r
Synopsis: Exact Matching and Matching-Adjusted Indirect Comparison (MAIC)
Description:

The second version (0.2.0) contains implementation for exact matching which is an alternative to propensity score matching (see Glimm & Yau (2025)). The initial version (0.1.2) contains a collection of easy-to-implement tools for checking whether a MAIC can be conducted, as well as an alternative way of calculating weights (see Glimm & Yau (2021) <doi:10.1002/pst.2210>.).

r-mpr 1.0.6
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mpr
Licenses: GPL 3
Build system: r
Synopsis: Multi-Parameter Regression (MPR)
Description:

Fitting Multi-Parameter Regression (MPR) models to right-censored survival data. These are flexible parametric regression models which extend standard models, for example, proportional hazards. See Burke & MacKenzie (2016) <doi:10.1111/biom.12625> and Burke et al (2020) <doi:10.1111/rssc.12398>.

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