_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

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-lbreg 1.3
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=lbreg
Licenses: GPL 2
Build system: r
Synopsis: Log-Binomial Regression with Constrained Optimization
Description:

Maximum likelihood estimation of log-binomial regression with special functionality when the MLE is on the boundary of the parameter space.

r-logcondiscr 1.0.6
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 r-cobs@1.3-9-1
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: http://www.kasparrufibach.ch
Licenses: GPL 2+
Build system: r
Synopsis: Estimate a Log-Concave Probability Mass Function from Discrete i.i.d. Observations
Description:

Given independent and identically distributed observations X(1), ..., X(n), allows to compute the maximum likelihood estimator (MLE) of probability mass function (pmf) under the assumption that it is log-concave, see Weyermann (2007) and Balabdaoui, Jankowski, Rufibach, and Pavlides (2012). The main functions of the package are logConDiscrMLE that allows computation of the log-concave MLE, logConDiscrCI that computes pointwise confidence bands for the MLE, and kInflatedLogConDiscr that computes a mixture of a log-concave PMF and a point mass at k.

r-localscore 2.0.3
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=localScore
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Package for Sequence Analysis by Local Score
Description:

Functionalities for calculating the local score and calculating statistical relevance (p-value) to find a local Score in a sequence of given distribution (S. Mercier and J.-J. Daudin (2001) <https://hal.science/hal-00714174/>) ; S. Karlin and S. Altschul (1990) <https://pmc.ncbi.nlm.nih.gov/articles/PMC53667/> ; S. Mercier, D. Cellier and F. Charlot (2003) <https://hal.science/hal-00937529v1/> ; A. Lagnoux, S. Mercier and P. Valois (2017) <doi:10.1093/bioinformatics/btw699> ).

r-lmerperm 0.1.9
Propagated dependencies: r-lmertest@3.1-3
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=lmerPerm
Licenses: GPL 3
Build system: r
Synopsis: Perform Permutation Test on General Linear and Mixed Linear Regression
Description:

We provide a solution for performing permutation tests on linear and mixed linear regression models. It allows users to obtain accurate p-values without making distributional assumptions about the data. By generating a null distribution of the test statistics through repeated permutations of the response variable, permutation tests provide a powerful alternative to traditional parameter tests (Holt et al. (2023) <doi:10.1007/s10683-023-09799-6>). In this early version, we focus on the permutation tests over observed t values of beta coefficients, i.e.original t values generated by parameter tests. After generating a null distribution of the test statistic through repeated permutations of the response variable, each observed t values would be compared to the null distribution to generate a p-value. To improve the efficiency,a stop criterion (Anscombe (1953) <doi:10.1111/j.2517-6161.1953.tb00121.x>) is adopted to force permutation to stop if the estimated standard deviation of the value falls below a fraction of the estimated p-value. By doing so, we avoid the need for massive calculations in exact permutation methods while still generating stable and accurate p-values.

r-lmerconveniencefunctions 3.0
Propagated dependencies: r-mgcv@1.9-4 r-matrix@1.7-4 r-lme4@1.1-37 r-lcfdata@2.0 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://cran.r-project.org/package=LMERConvenienceFunctions
Licenses: GPL 2
Build system: r
Synopsis: Model Selection and Post-Hoc Analysis for (G)LMER Models
Description:

The main function of the package is to perform backward selection of fixed effects, forward fitting of the random effects, and post-hoc analysis using parallel capabilities. Other functionality includes the computation of ANOVAs with upper- or lower-bound p-values and R-squared values for each model term, model criticism plots, data trimming on model residuals, and data visualization. The data to run examples is contained in package LCF_data.

r-lightsout 0.3.2
Propagated dependencies: r-shinyjs@2.1.0 r-shiny@1.11.1 r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/daattali/lightsout
Licenses: Expat
Build system: r
Synopsis: Implementation of the 'Lights Out' Puzzle Game
Description:

Lights Out is a puzzle game consisting of a grid of lights that are either on or off. Pressing any light will toggle it and its adjacent lights. The goal of the game is to switch all the lights off. This package provides an interface to play the game on different board sizes, both through the command line or with a visual application. Puzzles can also be solved using the automatic solver included. View a demo online at <https://daattali.com/shiny/lightsout/>.

r-lans2r 1.2.0
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-reshape2@1.4.5 r-r-matlab@3.7.0 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/KopfLab/lans2r
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Work with Look at NanoSIMS Data in R
Description:

R interface for working with nanometer scale secondary ion mass spectrometry (NanoSIMS) data exported from Look at NanoSIMS.

r-lorenzregression 2.3.0
Propagated dependencies: r-rsample@1.3.1 r-rearrangement@2.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-progress@1.2.3 r-parsnip@1.3.3 r-mass@7.3-65 r-ggplot2@4.0.1 r-ga@3.2.4 r-foreach@1.5.2 r-doparallel@1.0.17 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/l.scm (guix-cran packages l)
Home page: https://github.com/AlJacq/LorenzRegression
Licenses: GPL 3
Build system: r
Synopsis: Lorenz and Penalized Lorenz Regressions
Description:

Inference for the Lorenz and penalized Lorenz regressions. More broadly, the package proposes functions to assess inequality and graphically represent it. The Lorenz Regression procedure is introduced in Heuchenne and Jacquemain (2022) <doi:10.1016/j.csda.2021.107347> and in Jacquemain, A., C. Heuchenne, and E. Pircalabelu (2024) <doi:10.1214/23-EJS2200>.

r-magree 1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=magree
Licenses: GPL 3 GPL 2
Build system: r
Synopsis: Implements the O'Connell-Dobson-Schouten Estimators of Agreement for Multiple Observers
Description:

This package implements an interface to the legacy Fortran code from O'Connell and Dobson (1984) <DOI:10.2307/2531148>. Implements Fortran 77 code for the methods developed by Schouten (1982) <DOI:10.1111/j.1467-9574.1982.tb00774.x>. Includes estimates of average agreement for each observer and average agreement for each subject.

r-mlt-docreg 1.1-12
Propagated dependencies: r-truncreg@0.2-5 r-survival@3.8-3 r-numderiv@2016.8-1.1 r-multcomp@1.4-29 r-mlt@1.7-3 r-lattice@0.22-7 r-flexsurv@2.3.2 r-eha@2.11.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://ctm.R-forge.R-project.org
Licenses: GPL 2
Build system: r
Synopsis: Most Likely Transformations: Documentation and Regression Tests
Description:

Additional documentation, a package vignette and regression tests for package mlt.

r-mondrian 1.1.2
Propagated dependencies: r-rcolorbrewer@1.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=Mondrian
Licenses: GPL 2+
Build system: r
Synopsis: Simple Graphical Representation of the Relative Occurrence and Co-Occurrence of Events
Description:

The unique function of this package allows representing in a single graph the relative occurrence and co-occurrence of events measured in a sample. As examples, the package was applied to describe the occurrence and co-occurrence of different species of bacterial or viral symbionts infecting arthropods at the individual level. The graphics allows determining the prevalence of each symbiont and the patterns of multiple infections (i.e. how different symbionts share or not the same individual hosts). We named the package after the famous painter as the graphical output recalls Mondrianâ s paintings.

r-mrbayes 0.5.2
Propagated dependencies: r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-desctools@0.99.60 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/okezie94/mrbayes
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Summary Data Models for Mendelian Randomization Studies
Description:

Bayesian estimation of inverse variance weighted (IVW), Burgess et al. (2013) <doi:10.1002/gepi.21758>, and MR-Egger, Bowden et al. (2015) <doi:10.1093/ije/dyv080>, summary data models for Mendelian randomization analyses.

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-mltools 0.3.5
Propagated dependencies: r-matrix@1.7-4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ben519/mltools
Licenses: Expat
Build system: r
Synopsis: Machine Learning Tools
Description:

This package provides a collection of machine learning helper functions, particularly assisting in the Exploratory Data Analysis phase. Makes heavy use of the data.table package for optimal speed and memory efficiency. Highlights include a versatile bin_data() function, sparsify() for converting a data.table to sparse matrix format with one-hot encoding, fast evaluation metrics, and empirical_cdf() for calculating empirical Multivariate Cumulative Distribution Functions.

r-mcauchyd 1.3.3
Propagated dependencies: r-rgl@1.3.31 r-mass@7.3-65 r-lifecycle@1.0.4 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/mcauchyd
Licenses: GPL 3+
Build system: r
Synopsis: Multivariate Cauchy Distribution; Kullback-Leibler Divergence
Description:

Distance between multivariate Cauchy distributions, as presented by N. Bouhlel and D. Rousseau (2022) <doi:10.3390/e24060838>. Manipulation of multivariate Cauchy distributions.

r-matrixdist 1.1.9
Propagated dependencies: r-reshape2@1.4.5 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-nnet@7.3-20
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/martinbladt/matrixdist_1.0
Licenses: GPL 3
Build system: r
Synopsis: Statistics for Matrix Distributions
Description:

This package provides tools for phase-type distributions including the following variants: continuous, discrete, multivariate, in-homogeneous, right-censored, and regression. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided for all models. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm, Olsson, M. (1996). Estimation of phase-type distributions from censored data, Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60>, Albrecher, H., Bladt, M., & Yslas, J. (2022) <doi:10.1111/sjos.12505>, Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022) <doi:10.1016/j.insmatheco.2022.08.001>, Bladt, M., & Yslas, J. (2022) <doi:10.1080/03461238.2022.2097019>, Bladt, M. (2022) <doi:10.1017/asb.2021.40>, Bladt, M. (2023) <doi:10.1080/10920277.2023.2167833>, Albrecher, H., Bladt, M., & Mueller, A. (2023) <doi:10.1515/demo-2022-0153>, Bladt, M. & Yslas, J. (2023) <doi:10.1016/j.insmatheco.2023.02.008>.

r-metabodata 0.6.3
Propagated dependencies: r-yaml@2.3.10 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-piggyback@0.1.5 r-magrittr@2.0.4 r-fs@1.6.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://aberhrml.github.io/metaboData/
Licenses: GPL 3+
Build system: r
Synopsis: Example Metabolomics Data Sets
Description:

Data sets from a variety of biological sample matrices, analysed using a number of mass spectrometry based metabolomic analytical techniques. The example data sets are stored remotely using GitHub releases <https://github.com/aberHRML/metaboData/releases> which can be accessed from R using the package. The package also includes the abr1 FIE-MS data set from the FIEmspro package <https://users.aber.ac.uk/jhd/> <doi:10.1038/nprot.2007.511>.

r-mpsem 0.6-1
Propagated dependencies: r-mass@7.3-65 r-magrittr@2.0.4 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MPSEM
Licenses: GPL 3
Build system: r
Synopsis: Modelling Phylogenetic Signals using Eigenvector Maps
Description:

Computational tools to represent phylogenetic signals using adapted eigenvector maps.

r-mseapca 2.2.1
Propagated dependencies: r-xml@3.99-0.20 r-loadings@0.5.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mseapca
Licenses: LGPL 3
Build system: r
Synopsis: Metabolite Set Enrichment Analysis for Loadings
Description:

Computing metabolite set enrichment analysis (MSEA) (Yamamoto, H. et al. (2014) <doi:10.1186/1471-2105-15-51>), single sample enrichment analysis (SSEA) (Yamamoto, H. (2023) <doi:10.51094/jxiv.262>) and over-representation analysis (ORA) that accounts for undetected metabolites (Yamamoto, H. (2024) <doi:10.51094/jxiv.954>).

r-manet 2.0
Propagated dependencies: r-mcmcpack@1.7-1 r-mclust@6.1.2 r-igraph@2.2.1 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=manet
Licenses: GPL 2
Build system: r
Synopsis: Multiple Allocation Model for Actor-Event Networks
Description:

Mixture model with overlapping clusters for binary actor-event data. Parameters are estimated in a Bayesian framework. Model and inference are described in Ranciati, Vinciotti, Wit (2017) Modelling actor-event network data via a mixture model under overlapping clusters. Submitted.

r-mark 0.8.3
Propagated dependencies: r-rlang@1.1.6 r-magrittr@2.0.4 r-fuj@0.2.2 r-fs@1.6.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://CRAN.R-project.org/package=mark
Licenses: Expat
Build system: r
Synopsis: Miscellaneous, Analytic R Kernels
Description:

Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.

r-mnlr 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-rmarkdown@2.30 r-nnet@7.3-20 r-e1071@1.7-16 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=MNLR
Licenses: GPL 2
Build system: r
Synopsis: Interactive Shiny Presentation for Working with Multinomial Logistic Regression
Description:

An interactive presentation on the topic of Multinomial Logistic Regression. It is helpful to those who want to learn Multinomial Logistic Regression quickly and get a hands on experience. The presentation has a template for solving problems on Multinomial Logistic Regression. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/MultinomPresentation>.

r-misspi 0.1.1
Propagated dependencies: r-sis@0.8-8 r-plotly@4.11.0 r-lightgbm@4.6.0 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dosnow@1.0.20 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/catstats/misspi
Licenses: GPL 2
Build system: r
Synopsis: Missing Value Imputation in Parallel
Description:

This package provides a framework that boosts the imputation of missForest by Stekhoven, D.J. and Bühlmann, P. (2012) <doi:10.1093/bioinformatics/btr597> by harnessing parallel processing and through the fast Gradient Boosted Decision Trees (GBDT) implementation LightGBM by Ke, Guolin et al.(2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. misspi has the following main advantages: 1. Allows embrassingly parallel imputation on large scale data. 2. Accepts a variety of machine learning models as methods with friendly user portal. 3. Supports multiple initializations methods. 4. Supports early stopping that prohibits unnecessary iterations.

r-mrfcov 1.0.39
Propagated dependencies: r-sfsmisc@1.1-23 r-reshape2@1.4.5 r-purrr@1.2.0 r-plyr@1.8.9 r-pbapply@1.7-4 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-igraph@2.2.1 r-gridextra@2.3 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/nicholasjclark/MRFcov
Licenses: GPL 3
Build system: r
Synopsis: Markov Random Fields with Additional Covariates
Description:

Approximate node interaction parameters of Markov Random Fields graphical networks. Models can incorporate additional covariates, allowing users to estimate how interactions between nodes in the graph are predicted to change across covariate gradients. The general methods implemented in this package are described in Clark et al. (2018) <doi:10.1002/ecy.2221>.

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