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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-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-msamp 1.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=msamp
Licenses: FSDG-compatible
Build system: r
Synopsis: Estimate Sample Size to Detect Bacterial Contamination in a Product Lot
Description:

Estimates the sample size needed to detect microbial contamination in a lot with a user-specified detection probability and user-specified analytical sensitivity. Various patterns of microbial contamination are accounted for: homogeneous (Poisson), heterogeneous (Poisson-Gamma) or localized(Zero-inflated Poisson). Ida Jongenburger et al. (2010) <doi:10.1016/j.foodcont.2012.02.004> "Impact of microbial distributions on food safety". Leroy Simon (1963) <doi:10.1017/S0515036100001975> "Casualty Actuarial Society - The Negative Binomial and Poisson Distributions Compared".

r-mmsample 0.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 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=mmsample
Licenses: GPL 3
Build system: r
Synopsis: Multivariate Matched Sampling
Description:

Subset a control group to match an intervention group on a set of features using multivariate matching and propensity score calipers. Based on methods in Rosenbaum and Rubin (1985).

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-mtarm 0.1.8
Propagated dependencies: r-progressr@0.18.0 r-mvtnorm@1.3-3 r-gigrvg@0.8 r-future-apply@1.20.0 r-future@1.68.0 r-formula@1.2-5 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/lhvanegasp/mtarm
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Bayesian Estimation of Multivariate Threshold Autoregressive Models
Description:

Estimation, inference and forecasting using the Bayesian approach for multivariate threshold autoregressive (TAR) models in which the distribution used to describe the noise process belongs to the class of Gaussian variance mixtures.

r-manifestor 1.6.2
Propagated dependencies: r-tm@0.7-16 r-tidyselect@1.2.1 r-tibble@3.3.0 r-readr@2.1.6 r-purrr@1.2.0 r-nlp@0.3-2 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-functional@0.6 r-dplyr@1.1.4 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://manifesto-project.wzb.eu/manifestoR
Licenses: GPL 3+
Build system: r
Synopsis: Access and Process Data and Documents of the Manifesto Project
Description:

This package provides access to coded election programmes from the Manifesto Corpus and to the Manifesto Project's Main Dataset and routines to analyse this data. The Manifesto Project <https://manifesto-project.wzb.eu> collects and analyses election programmes across time and space to measure the political preferences of parties. The Manifesto Corpus contains the collected and annotated election programmes in the Corpus format of the package tm to enable easy use of text processing and text mining functionality. Specific functions for scaling of coded political texts are included.

r-mkinfer 1.3
Propagated dependencies: r-rlang@1.1.6 r-nlme@3.1-168 r-mkdescr@0.9 r-miceadds@3.18-36 r-ggplot2@4.0.1 r-exactranktests@0.8-35 r-boot@1.3-32 r-arrangements@1.1.9
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/stamats/MKinfer
Licenses: LGPL 3
Build system: r
Synopsis: Inferential Statistics
Description:

Computation of various confidence intervals (Altman et al. (2000), ISBN:978-0-727-91375-3; Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) including bootstrapped versions (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) as well as Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2), permutation (Janssen (1997), <doi:10.1016/S0167-7152(97)00043-6>), bootstrap (Davison and Hinkley (1997), ISBN:978-0-511-80284-3), intersection-union (Sozu et al. (2015), ISBN:978-3-319-22005-5) and multiple imputation (Barnard and Rubin (1999), <doi:10.1093/biomet/86.4.948>) t-test; furthermore, computation of intersection-union z-test as well as multiple imputation Wilcoxon tests. Graphical visualizations: volcano plot, Bland-Altman plots (Bland and Altman (1986), <doi:10.1016/S0140-6736(86)90837-8>; Shieh (2018), <doi:10.1186/s12874-018-0505-y>), mean difference plot (Boehning et al. (2008), <doi:10.1177/0962280207081867>), plot of test statistic for permutation and bootstrap tests as well as objects of class htest.

r-modelobj 4.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=modelObj
Licenses: GPL 2
Build system: r
Synopsis: Model Object Framework for Regression Analysis
Description:

This package provides a utility library to facilitate the generalization of statistical methods built on a regression framework. Package developers can use modelObj methods to initiate a regression analysis without concern for the details of the regression model and the method to be used to obtain parameter estimates. The specifics of the regression step are left to the user to define when calling the function. The user of a function developed within the modelObj framework creates as input a modelObj that contains the model and the R methods to be used to obtain parameter estimates and to obtain predictions. In this way, a user can easily go from linear to non-linear models within the same package.

r-mlmodelselection 1.0
Propagated dependencies: r-rcppdist@0.1.1.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/kuojunglee/
Licenses: GPL 2
Build system: r
Synopsis: Model Selection in Multivariate Longitudinal Data Analysis
Description:

An efficient Gibbs sampling algorithm is developed for Bayesian multivariate longitudinal data analysis with the focus on selection of important elements in the generalized autoregressive matrix. It provides posterior samples and estimates of parameters. In addition, estimates of several information criteria such as Akaike information criterion (AIC), Bayesian information criterion (BIC), deviance information criterion (DIC) and prediction accuracy such as the marginal predictive likelihood (MPL) and the mean squared prediction error (MSPE) are provided for model selection.

r-mixmatrix 0.2.8
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-glue@1.8.0 r-cholwishart@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/gzt/MixMatrix/
Licenses: GPL 3
Build system: r
Synopsis: Classification with Matrix Variate Normal and t Distributions
Description:

This package provides sampling and density functions for matrix variate normal, t, and inverted t distributions; ML estimation for matrix variate normal and t distributions using the EM algorithm, including some restrictions on the parameters; and classification by linear and quadratic discriminant analysis for matrix variate normal and t distributions described in Thompson et al. (2019) <doi:10.1080/10618600.2019.1696208>. Performs clustering with matrix variate normal and t mixture models.

r-mailr 0.8
Dependencies: openjdk@25
Propagated dependencies: r-stringr@1.6.0 r-rjava@1.0-11 r-r-utils@2.13.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/rpremrajGit/mailR
Licenses: GPL 3
Build system: r
Synopsis: Utility to Send Emails from R
Description:

Interface to Apache Commons Email to send emails from R.

r-multinets 0.2.2
Propagated dependencies: r-rcpp@1.1.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/neylsoncrepalde/multinets
Licenses: GPL 3
Build system: r
Synopsis: Multilevel Networks Analysis
Description:

Analyze multilevel networks as described in Lazega et al (2008) <doi:10.1016/j.socnet.2008.02.001> and in Lazega and Snijders (2016, ISBN:978-3-319-24520-1). The package was developed essentially as an extension to igraph'.

r-multiwayregression 1.2
Propagated dependencies: 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=MultiwayRegression
Licenses: GPL 3
Build system: r
Synopsis: Perform Tensor-on-Tensor Regression
Description:

This package provides functions to predict one multi-way array (i.e., a tensor) from another multi-way array, using a low-rank CANDECOMP/PARAFAC (CP) factorization and a ridge (L_2) penalty [Lock, EF (2018) <doi:10.1080/10618600.2017.1401544>]. Also includes functions to sample from the Bayesian posterior of a tensor-on-tensor model.

r-maoea 0.6.2
Dependencies: python-numpy@1.26.4
Propagated dependencies: r-stringr@1.6.0 r-reticulate@1.44.1 r-randtoolbox@2.0.5 r-pracma@2.4.6 r-nsga2r@1.1 r-nnet@7.3-20 r-mass@7.3-65 r-lhs@1.2.0 r-gtools@3.9.5 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/dots26/MaOEA
Licenses: GPL 3+
Build system: r
Synopsis: Many Objective Evolutionary Algorithm
Description:

This package provides a set of evolutionary algorithms to solve many-objective optimization. Hybridization between the algorithms are also facilitated. Available algorithms are: SMS-EMOA <doi:10.1016/j.ejor.2006.08.008> NSGA-III <doi:10.1109/TEVC.2013.2281535> MO-CMA-ES <doi:10.1145/1830483.1830573> The following many-objective benchmark problems are also provided: DTLZ1'-'DTLZ4 from Deb, et al. (2001) <doi:10.1007/1-84628-137-7_6> and WFG4'-'WFG9 from Huband, et al. (2005) <doi:10.1109/TEVC.2005.861417>.

r-mbrm 0.1.1
Propagated dependencies: r-tibble@3.3.0 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-formula@1.2-5 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=MBRM
Licenses: GPL 3
Build system: r
Synopsis: Mixed Regression Models with Generalized Log-Gamma Random Effects
Description:

Multivariate distribution derived from a Bernoulli mixed model under a marginal approach, incorporating a non-normal random intercept whose distribution is assumed to follow a generalized log-gamma (GLG) specification under a particular parameter setting. Estimation is performed by maximizing the log-likelihood using numerical optimization techniques (Lizandra C. Fabio, Vanessa Barros, Cristian Lobos, Jalmar M. F. Carrasco, Marginal multivariate approach: A novel strategy for handling correlated binary outcomes, 2025, under submission).

r-multibridge 1.3.0
Dependencies: mpfr@4.2.2 gmp@6.3.0
Propagated dependencies: r-stringr@1.6.0 r-rdpack@2.6.4 r-rcpp@1.1.0 r-purrr@1.2.0 r-progress@1.2.3 r-mvtnorm@1.3-3 r-magrittr@2.0.4 r-coda@0.19-4.1 r-brobdingnag@1.2-9
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/asarafoglou/multibridge/
Licenses: GPL 2
Build system: r
Synopsis: Evaluating Multinomial Order Restrictions with Bridge Sampling
Description:

Evaluate hypotheses concerning the distribution of multinomial proportions using bridge sampling. The bridge sampling routine is able to compute Bayes factors for hypotheses that entail inequality constraints, equality constraints, free parameters, and mixtures of all three. These hypotheses are tested against the encompassing hypothesis, that all parameters vary freely or against the null hypothesis that all category proportions are equal. For more information see Sarafoglou et al. (2020) <doi:10.31234/osf.io/bux7p>.

r-makeit 1.0.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/arni-magnusson/makeit
Licenses: GPL 3
Build system: r
Synopsis: Run R Scripts if Needed
Description:

Automation tool to run R scripts if needed, based on last modified time. It comes with no package dependencies, organizational overhead, or structural requirements. In short: run an R script if underlying files have changed, otherwise do nothing.

r-mero 0.1.2
Propagated dependencies: r-progress@1.2.3 r-missforest@1.6.1 r-ggpubr@0.6.2 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=MERO
Licenses: GPL 3
Build system: r
Synopsis: Performing Monte Carlo Expectation Maximization Random Forest Imputation for Biological Data
Description:

Perform missing value imputation for biological data using the random forest algorithm, the imputation aim to keep the original mean and standard deviation consistent after imputation.

r-multirobust 1.0.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiRobust
Licenses: GPL 2+
Build system: r
Synopsis: Multiply Robust Methods for Missing Data Problems
Description:

Multiply robust estimation for population mean (Han and Wang 2013) <doi:10.1093/biomet/ass087>, regression analysis (Han 2014) <doi:10.1080/01621459.2014.880058> (Han 2016) <doi:10.1111/sjos.12177> and quantile regression (Han et al. 2019) <doi:10.1111/rssb.12309>.

r-metasubtract 1.60
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MetaSubtract
Licenses: GPL 3+
Build system: r
Synopsis: Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results
Description:

If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. The validation cohort needs to be independent from the meta-Genome-Wide-Association-Study (meta-GWAS) results. MetaSubtract will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. It can also handle different meta-analysis methods. It can be used for whole GWAS, but also for a limited set of genetic markers. See for application: Nolte I.M. et al. (2017); <doi: 10.1038/ejhg.2017.50>.

r-mpmsim 3.2.1
Propagated dependencies: r-reshape@0.8.10 r-rcompadre@1.4.0 r-rage@1.8.0 r-popdemo@1.3-2 r-popbio@2.8 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://jonesor.github.io/mpmsim/
Licenses: CC-BY-SA 4.0
Build system: r
Synopsis: Simulation of Matrix Population Models with Defined Life History Characteristics
Description:

Allows users to simulate matrix population models with particular characteristics based on aspects of life history such as mortality trajectories and fertility trajectories. Also allows the exploration of sampling error due to small sample size.

r-mreg 1.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/shug0131/mreg
Licenses: GPL 3+
Build system: r
Synopsis: Fits Regression Models When the Outcome is Partially Missing
Description:

This package implements the methods described in Bond S, Farewell V, 2006, Exact Likelihood Estimation for a Negative Binomial Regression Model with Missing Outcomes, Biometrics.

r-medicare 0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://www.github.com/robertgambrel/medicare
Licenses: Expat
Build system: r
Synopsis: Tools for Obtaining and Cleaning Medicare Public Use Files
Description:

Publicly available data from Medicare frequently requires extensive initial effort to extract desired variables and merge them; this package formalizes the techniques I've found work best. More information on the Medicare program, as well as guidance for the publicly available data this package targets, can be found on CMS's website covering publicly available data. See <https://www.cms.gov/Research-Statistics-Data-and-Systems/Research-Statistics-Data-and-Systems.html>.

r-malan 1.0.4
Propagated dependencies: r-tidygraph@1.3.1 r-tibble@3.3.0 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-magrittr@2.0.4 r-igraph@2.2.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mikldk.github.io/malan/
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: MAle Lineage ANalysis
Description:

MAle Lineage ANalysis by simulating genealogies backwards and imposing short tandem repeats (STR) mutations forwards. Intended for forensic Y chromosomal STR (Y-STR) haplotype analyses. Numerous analyses are possible, e.g. number of matches and meiotic distance to matches. Refer to papers mentioned in citation("malan") (DOI's: <doi:10.1371/journal.pgen.1007028>, <doi:10.21105/joss.00684> and <doi:10.1016/j.fsigen.2018.10.004>).

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