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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-mrmre 2.1.2.2
Propagated dependencies: r-survival@3.8-3 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.pmgenomics.ca/bhklab/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Parallelized Minimum Redundancy, Maximum Relevance (mRMR)
Description:

Computes mutual information matrices from continuous, categorical and survival variables, as well as feature selection with minimum redundancy, maximum relevance (mRMR) and a new ensemble mRMR technique. Published in De Jay et al. (2013) <doi:10.1093/bioinformatics/btt383>.

r-meddietcalc 0.1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MedDietCalc
Licenses: GPL 3
Build system: r
Synopsis: Multi Calculator to Compute Scores of Adherence to Mediterranean Diet
Description:

Multi Calculator of different scores to measure adherence to Mediterranean Diet, to compute them in nutriepidemiological data. Additionally, a sample dataset of this kind of data is provided, and some other minor tools useful in epidemiological studies.

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-msrdt 0.1.0
Propagated dependencies: r-reshape2@1.4.5 r-gtools@3.9.5 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ericchen12377/MSRDT
Licenses: GPL 3
Build system: r
Synopsis: Multi-State Reliability Demonstration Tests (MSRDT)
Description:

This is a implementation of design methods for multi-state reliability demonstration tests (MSRDT) with failure count data, which is associated with the work from the published paper "Multi-state Reliability Demonstration Tests" by Suiyao Chen et al. (2017) <doi:10.1080/08982112.2017.1314493>. It implements two types of MSRDT, multiple periods (MP) and multiple failure modes (MFM). For MP, two different scenarios with criteria on cumulative periods (Cum) or separate periods (Sep) are implemented respectively. It also provides the implementation of conventional design method, namely binomial tests for failure count data.

r-mwcsr 0.1.10
Dependencies: openjdk@25
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/ctlab/mwcsr
Licenses: Expat
Build system: r
Synopsis: Solvers for Maximum Weight Connected Subgraph Problem and Its Variants
Description:

Algorithms for solving various Maximum Weight Connected Subgraph Problems, including variants with budget constraints, cardinality constraints, weighted edges and signals. The package represents an R interface to high-efficient solvers based on relax-and-cut approach (Ã lvarez-Miranda E., Sinnl M. (2017) <doi:10.1016/j.cor.2017.05.015>) mixed-integer programming (Loboda A., Artyomov M., and Sergushichev A. (2016) <doi:10.1007/978-3-319-43681-4_17>) and simulated annealing.

r-modelltest 1.0.5
Propagated dependencies: r-survival@3.8-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-quantreg@6.1 r-mass@7.3-65 r-coxrobust@1.0.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ShanaScogin/modeLLtest
Licenses: GPL 3
Build system: r
Synopsis: Compare Models with Cross-Validated Log-Likelihood
Description:

An implementation of the cross-validated difference in means (CVDM) test by Desmarais and Harden (2014) <doi:10.1007/s11135-013-9884-7> (see also Harden and Desmarais, 2011 <doi:10.1177/1532440011408929>) and the cross-validated median fit (CVMF) test by Desmarais and Harden (2012) <doi:10.1093/pan/mpr042>. These tests use leave-one-out cross-validated log-likelihoods to assist in selecting among model estimations. You can also utilize data from Golder (2010) <doi:10.1177/0010414009341714> and Joshi & Mason (2008) <doi:10.1177/0022343308096155> that are included to facilitate examples from real-world analysis.

r-mlbplotr 1.2.0
Propagated dependencies: r-scales@1.4.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-magick@2.9.0 r-lifecycle@1.0.4 r-httr@1.4.7 r-gt@1.3.0 r-ggplot2@4.0.1 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/camdenk/mlbplotR
Licenses: Expat
Build system: r
Synopsis: Create 'ggplot2' and 'gt' Visuals with Major League Baseball Logos
Description:

This package provides tools to help visualize Major League Baseball analysis in ggplot2 and gt'. You provide team/player information and mlbplotR will transform that information into team colors, logos, or player headshots for graphics.

r-microbialgrowth 1.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MicrobialGrowth
Licenses: GPL 3+
Build system: r
Synopsis: Estimates Growth Parameters from Models and Plots the Curve
Description:

Fit growth curves to various known microbial growth models automatically to estimate growth parameters. Growth curves can be plotted with their uncertainty band. Growth models are: modified Gompertz model (Zwietering et al. (1990) <doi:10.1128/aem.56.6.1875-1881.1990>), Baranyi model (Baranyi and Roberts (1994) <doi:10.1016/0168-1605%2894%2990157-0>), Rosso model (Rosso et al. (1993) <doi:10.1006/jtbi.1993.1099>) and linear model (Dantigny (2005) <doi:10.1016/j.ijfoodmicro.2004.10.013>).

r-matman 1.1.4
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-shinywidgets@0.9.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-plotly@4.11.0 r-parsedate@1.3.2 r-lubridate@1.9.4 r-forecast@8.24.0 r-dt@0.34.0 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=matman
Licenses: GPL 3
Build system: r
Synopsis: Material Management
Description:

This package provides a set of functions, classes and methods for performing ABC and ABC/XYZ analyses, identifying overperforming, underperforming and constantly performing items, and plotting, analyzing as well as predicting the temporal development of items.

r-modernboot 0.1.1
Propagated dependencies: r-future-apply@1.20.0 r-future@1.68.0 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ikrakib/modernBoot
Licenses: Expat
Build system: r
Synopsis: Modern Resampling Methods: Bootstraps, Wild, Block, Permutation, and Selection Guidance
Description:

This package implements modern resampling and permutation methods for robust statistical inference without restrictive parametric assumptions. Provides bias-corrected and accelerated (BCa) bootstrap (Efron and Tibshirani (1993) <doi:10.1201/9780429246593>), wild bootstrap for heteroscedastic regression (Liu (1988) <doi:10.1214/aos/1176351062>, Davidson and Flachaire (2008) <doi:10.1016/j.jeconom.2008.08.003>), block bootstrap for time series (Politis and Romano (1994) <doi:10.1080/01621459.1994.10476870>), and permutation-based multiple testing correction (Westfall and Young (1993) <ISBN:0-471-55761-7>). Methods handle non-normal data, heteroscedasticity, time series correlation, and multiple comparisons.

r-manynet 1.7.0
Propagated dependencies: r-tidygraph@1.3.1 r-pillar@1.11.1 r-network@1.19.0 r-igraph@2.2.1 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://stocnet.github.io/manynet/
Licenses: Expat
Build system: r
Synopsis: Many Ways to Make, Modify, Mark, and Measure Myriad Networks
Description:

Many tools for making, modifying, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and igraph', network', and tidygraph objects, on directed, multiplex, multimodal, signed, and other networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing networks with sensible defaults.

r-mrfa 0.6
Propagated dependencies: r-randtoolbox@2.0.5 r-plyr@1.8.9 r-grplasso@0.4-7 r-glmnet@4.1-10 r-foreach@1.5.2 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MRFA
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Fitting and Predicting Large-Scale Nonlinear Regression Problems using Multi-Resolution Functional ANOVA (MRFA) Approach
Description:

This package performs the MRFA approach proposed by Sung et al. (2020) <doi:10.1080/01621459.2019.1595630> to fit and predict nonlinear regression problems, particularly for large-scale and high-dimensional problems. The application includes deterministic or stochastic computer experiments, spatial datasets, and so on.

r-marginme 0.1.0
Propagated dependencies: r-glmmrbase@1.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/samuel-watson/marginme
Licenses: GPL 2+
Build system: r
Synopsis: Estimation of Relative Risks, Risk Differences, and Marginal Effects from Mixed Models Using Marginal Standardization
Description:

Functionality to estimate relative risks, risk differences, and partial effects from mixed model. Marginalisation over random effect terms is accomplished using Markov Chain Monte Carlo.

r-multimarker 1.0.1
Propagated dependencies: r-truncnorm@1.0-9 r-ordinalnet@2.13
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multiMarker
Licenses: GPL 2+
Build system: r
Synopsis: Latent Variable Model to Infer Food Intake from Multiple Biomarkers
Description:

This package provides a latent variable model based on factor analytic and mixture of experts models, designed to infer food intake from multiple biomarkers data. The model is framed within a Bayesian hierarchical framework, which provides flexibility to adapt to different biomarker distributions and facilitates inference on food intake from biomarker data alone, along with the associated uncertainty. Details are in D'Angelo, et al. (2020) <arXiv:2006.02995>.

r-massextra 1.2.2
Propagated dependencies: r-mass@7.3-65 r-demokde@1.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MASSExtra
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Some 'MASS' Enhancements
Description:

Some enhancements, extensions and additions to the facilities of the recommended MASS package that are useful mainly for teaching purposes, with more convenient default settings and user interfaces. Key functions from MASS are imported and re-exported to avoid masking conflicts. In addition we provide some additional functions mainly used to illustrate coding paradigms and techniques, such as Gramm-Schmidt orthogonalisation and generalised eigenvalue problems.

r-mtsys 1.2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/okayaa/MTSYS
Licenses: Expat
Build system: r
Synopsis: Methods in Mahalanobis-Taguchi (MT) System
Description:

Mahalanobis-Taguchi (MT) system is a collection of multivariate analysis methods developed for the field of quality engineering. MT system consists of two families depending on their purpose. One is a family of Mahalanobis-Taguchi (MT) methods (in the broad sense) for diagnosis (see Woodall, W. H., Koudelik, R., Tsui, K. L., Kim, S. B., Stoumbos, Z. G., and Carvounis, C. P. (2003) <doi:10.1198/004017002188618626>) and the other is a family of Taguchi (T) methods for forecasting (see Kawada, H., and Nagata, Y. (2015) <doi:10.17929/tqs.1.12>). The MT package contains three basic methods for the family of MT methods and one basic method for the family of T methods. The MT method (in the narrow sense), the Mahalanobis-Taguchi Adjoint (MTA) methods, and the Recognition-Taguchi (RT) method are for the MT method and the two-sided Taguchi (T1) method is for the family of T methods. In addition, the Ta and Tb methods, which are the improved versions of the T1 method, are included.

r-mmoc 0.1.1.0
Propagated dependencies: r-spectrum@1.1 r-mass@7.3-65 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MMOC
Licenses: Expat
Build system: r
Synopsis: Multi-Omic Spectral Clustering using the Flag Manifold
Description:

Multi-omic (or any multi-view) spectral clustering methods often assume the same number of clusters across all datasets. We supply methods for multi-omic spectral clustering when the number of distinct clusters differs among the omics profiles (views).

r-mnp 3.1-5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/kosukeimai/MNP
Licenses: GPL 2+
Build system: r
Synopsis: Fitting the Multinomial Probit Model
Description:

Fits the Bayesian multinomial probit model via Markov chain Monte Carlo. The multinomial probit model is often used to analyze the discrete choices made by individuals recorded in survey data. Examples where the multinomial probit model may be useful include the analysis of product choice by consumers in market research and the analysis of candidate or party choice by voters in electoral studies. The MNP package can also fit the model with different choice sets for each individual, and complete or partial individual choice orderings of the available alternatives from the choice set. The estimation is based on the efficient marginal data augmentation algorithm that is developed by Imai and van Dyk (2005). "A Bayesian Analysis of the Multinomial Probit Model Using the Data Augmentation." Journal of Econometrics, Vol. 124, No. 2 (February), pp. 311-334. <doi:10.1016/j.jeconom.2004.02.002> Detailed examples are given in Imai and van Dyk (2005). "MNP: R Package for Fitting the Multinomial Probit Model." Journal of Statistical Software, Vol. 14, No. 3 (May), pp. 1-32. <doi:10.18637/jss.v014.i03>.

r-mpv 2.0
Propagated dependencies: r-lattice@0.22-7 r-kernsmooth@2.23-26
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MPV
Licenses: FSDG-compatible
Build system: r
Synopsis: Data Sets from Montgomery, Peck and Vining
Description:

Most of this package consists of data sets from the textbook Introduction to Linear Regression Analysis (3rd ed), by Montgomery, Peck and Vining. Some additional data sets and functions are also included.

r-magui 4.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=maGUI
Licenses: GPL 2
Build system: r
Synopsis: Graphical User Interface for Microarray Data Analysis and Annotation
Description:

This package provides a comprehensive graphical user interface for analysis of Affymetrix, Agilent, Illumina, Nimblegen and other microarray data. It can perform miscellaneous tasks such as gene set enrichment and test analyses, identifying gene symbols and building co-expression network. It can also estimate sample size for atleast two-fold expression change. The current version is its slenderized form for compatable and flexible implementation.

r-mobilityindexr 0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mobilityIndexR
Licenses: Expat
Build system: r
Synopsis: Calculates Transition Matrices and Mobility Indices
Description:

Measures mobility in a population through transition matrices and mobility indices. Relative, mixed, and absolute transition matrices are supported. The Prais-Bibby, Absolute Movement, Origin Specific, and Weighted Group Mobility indices are supported. Example income and grade data are included.

r-mobps 1.13.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MoBPS
Licenses: GPL 3+
Build system: r
Synopsis: Modular Breeding Program Simulator
Description:

Framework for the simulation framework for the simulation of complex breeding programs and compare their economic and genetic impact. Associated publication: Pook et al. (2020) <doi:10.1534/g3.120.401193>.

r-multinomialci 1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://ccia.ugr.es/~pjvi/
Licenses: LGPL 3+
Build system: r
Synopsis: Simultaneous Confidence Intervals for Multinomial Proportions According to the Method by Sison and Glaz
Description:

An implementation of a method for building simultaneous confidence intervals for the probabilities of a multinomial distribution given a set of observations, proposed by Sison and Glaz in their paper: Sison, C.P and J. Glaz. Simultaneous confidence intervals and sample size determination for multinomial proportions. Journal of the American Statistical Association, 90:366-369 (1995). The method is an R translation of the SAS code implemented by May and Johnson in their paper: May, W.L. and W.D. Johnson. Constructing two-sided simultaneous confidence intervals for multinomial proportions for small counts in a large number of cells. Journal of Statistical Software 5(6) (2000). Paper and code available at <DOI:10.18637/jss.v005.i06>.

r-mrds 3.0.1
Propagated dependencies: r-rsolnp@2.0.1 r-rdpack@2.6.4 r-optimx@2025-4.9 r-numderiv@2016.8-1.1 r-nloptr@2.2.1 r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/DistanceDevelopment/mrds/
Licenses: GPL 2+
Build system: r
Synopsis: Mark-Recapture Distance Sampling
Description:

Animal abundance estimation via conventional, multiple covariate and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator.

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Total results: 68658