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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-multe 1.1.0
Propagated dependencies: r-nnet@7.3-20
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/kolesarm/multe
Licenses: Expat
Build system: r
Synopsis: Multiple Treatment Effects Regression
Description:

This package implements contamination bias diagnostics and alternative estimators for regressions with multiple treatments. The implementation is based on Goldsmith-Pinkham, Hull, and Kolesár (2024) <doi:10.48550/arXiv.2106.05024>.

r-memor 0.2.3
Propagated dependencies: r-yaml@2.3.10 r-rmarkdown@2.30 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/hebrewseniorlife/memor
Licenses: GPL 3
Build system: r
Synopsis: 'rmarkdown' Template that Can be Highly Customized
Description:

This package provides a rmarkdown template that supports company logo, contact info, watermarks and more. Currently restricted to Latex'/'Markdown'; a similar HTML theme will be added in the future.

r-mmmgee 1.20
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mmmgee
Licenses: GPL 3
Build system: r
Synopsis: Simultaneous Inference for Multiple Linear Contrasts in GEE Models
Description:

This package provides global hypothesis tests, multiple testing procedures and simultaneous confidence intervals for multiple linear contrasts of regression coefficients in a single generalized estimating equation (GEE) model or across multiple GEE models. GEE models are fit by a modified version of the geeM package.

r-mvlsw 1.2.5
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-wavethresh@4.7.3 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=mvLSW
Licenses: GPL 3+
Build system: r
Synopsis: Multivariate, Locally Stationary Wavelet Process Estimation
Description:

This package provides tools for analysing multivariate time series with wavelets. This includes: simulation of a multivariate locally stationary wavelet (mvLSW) process from a multivariate evolutionary wavelet spectrum (mvEWS); estimation of the mvEWS, local coherence and local partial coherence. See Park, Eckley and Ombao (2014) <doi:10.1109/TSP.2014.2343937> for details.

r-mclustcomp 0.3.5
Propagated dependencies: r-rdpack@2.6.4 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mclustcomp
Licenses: Expat
Build system: r
Synopsis: Measures for Comparing Clusters
Description:

Given a set of data points, a clustering is defined as a disjoint partition where each pair of sets in a partition has no overlapping elements. This package provides 25 methods that play a role somewhat similar to distance or metric that measures similarity of two clusterings - or partitions. For a more detailed description, see Meila, M. (2005) <doi:10.1145/1102351.1102424>.

r-methscope 1.0.0
Dependencies: zlib@1.3.1
Propagated dependencies: r-xgboost@1.7.11.1 r-uwot@0.2.4 r-tidyr@1.3.1 r-stringr@1.6.0 r-nnls@1.6 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-fnn@1.1.4.1 r-dplyr@1.1.4 r-doparallel@1.0.17 r-data-table@1.17.8 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=MethScope
Licenses: Expat
Build system: r
Synopsis: Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent Pattern Encoding
Description:

This package provides methods for analyzing DNA methylation data via Most Recurrent Methylation Patterns (MRMPs). Supports cell-type annotation, spatial deconvolution, unsupervised clustering, and cancer cell-of-origin inference. Includes C-backed summaries for YAME â .cg/.cmâ files (overlap counts, log2 odds ratios, beta/depth aggregation), an XGBoost classifier, NNLS deconvolution, and plotting utilities. Scales to large spatial and single-cell methylomes and is robust to extreme sparsity.

r-mgl 1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://sites.google.com/a/cs.washington.edu/mgl/
Licenses: GPL 2+
Build system: r
Synopsis: Module Graphical Lasso
Description:

An aggressive dimensionality reduction and network estimation technique for a high-dimensional Gaussian graphical model (GGM). Please refer to: Efficient Dimensionality Reduction for High-Dimensional Network Estimation, Safiye Celik, Benjamin A. Logsdon, Su-In Lee, Proceedings of The 31st International Conference on Machine Learning, 2014, p. 1953--1961.

r-mediak 1.0
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MediaK
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Calculate MeDiA_K Distance
Description:

Calculates MeDiA_K (means Mean Distance Association by K-nearest neighbor) in order to detect nonlinear associations.

r-mlgl 1.0.1
Propagated dependencies: r-paralleldist@0.2.7 r-matrix@1.7-4 r-mass@7.3-65 r-gglasso@1.6 r-fastcluster@1.3.0 r-factominer@2.12
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MLGL
Licenses: GPL 2+
Build system: r
Synopsis: Multi-Layer Group-Lasso
Description:

It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2023) <doi:10.18637/jss.v106.i03>).

r-multipleoutcomes 0.4
Propagated dependencies: r-survival@3.8-3 r-stringr@1.6.0 r-numderiv@2016.8-1.1 r-momentfit@1.0 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=multipleOutcomes
Licenses: Expat
Build system: r
Synopsis: Asymptotic Covariance Matrix of Regression Models for Multiple Outcomes
Description:

Regression models can be fitted for multiple outcomes simultaneously. This package computes estimates of parameters across fitted models and returns the matrix of asymptotic covariance. Various applications of this package, including CUPED (Controlled Experiments Utilizing Pre-Experiment Data), multiple comparison adjustment, are illustrated.

r-mlr3spatial 0.6.1
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-r6@2.6.1 r-mlr3misc@0.19.0 r-mlr3@1.2.0 r-lgr@0.5.0 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mlr3spatial.mlr-org.com
Licenses: LGPL 3
Build system: r
Synopsis: Support for Spatial Objects Within the 'mlr3' Ecosystem
Description:

Extends the mlr3 ML framework with methods for spatial objects. Data storage and prediction are supported for packages terra', raster and stars'.

r-molgenisarmadillo 2.9.3
Propagated dependencies: r-urltools@1.7.3.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlist@0.4.6.2 r-readr@2.1.6 r-purrr@1.2.0 r-molgenisauth@1.0.0 r-httr2@1.2.1 r-httr@1.4.7 r-dplyr@1.1.4 r-cli@3.6.5 r-base64enc@0.1-3 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/molgenis/molgenis-r-armadillo/
Licenses: LGPL 2.1+
Build system: r
Synopsis: Armadillo Client for the Armadillo Service
Description:

This package provides a set of functions to manage data shared on a MOLGENIS Armadillo server.

r-movecost 2.1
Propagated dependencies: r-terra@1.8-86 r-sp@2.2-0 r-sf@1.0-23 r-raster@3.6-32 r-matrix@1.7-4 r-gdistance@1.6.5 r-elevatr@0.99.1 r-chron@2.3-62
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=movecost
Licenses: GPL 2+
Build system: r
Synopsis: Calculation of Slope-Dependant Accumulated Cost Surface, Least-Cost Paths, Least-Cost Corridors, Least-Cost Networks Related to Human Movement Across the Landscape
Description:

This package provides the facility to calculate non-isotropic accumulated cost surface, least-cost paths, least-cost corridors, least-cost networks using a number of human-movement-related cost functions that can be selected by the user. It just requires a Digital Terrain Model, a start location and (optionally) destination locations. See Alberti (2019) <doi:10.1016/j.softx.2019.100331>.

r-multiridge 1.11
Propagated dependencies: r-survival@3.8-3 r-snowfall@1.84-6.3 r-proc@1.19.0.1 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=multiridge
Licenses: GPL 3+
Build system: r
Synopsis: Fast Cross-Validation for Multi-Penalty Ridge Regression
Description:

Multi-penalty linear, logistic and cox ridge regression, including estimation of the penalty parameters by efficient (repeated) cross-validation and marginal likelihood maximization. Multiple high-dimensional data types that require penalization are allowed, as well as unpenalized variables. Paired and preferential data types can be specified. See Van de Wiel et al. (2021), <arXiv:2005.09301>.

r-matskew 0.1.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MatSkew
Licenses: GPL 2+
Build system: r
Synopsis: Matrix Skew-T Parameter Estimation
Description:

This package performs matrix skew-t parameter estimation, Gallaugher and McNicholas (2017) <doi: 10.1002/sta4.143>.

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.

r-mvna 2.0.1
Propagated dependencies: r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mvna
Licenses: Expat
Build system: r
Synopsis: Nelson-Aalen Estimator of the Cumulative Hazard in Multistate Models
Description:

Computes the Nelson-Aalen estimator of the cumulative transition hazard for arbitrary Markov multistate models <ISBN:978-0-387-68560-1>.

r-multicmp 1.1
Propagated dependencies: r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://dx.doi.org/10.1016/j.jmva.2016.04.007
Licenses: GPL 3
Build system: r
Synopsis: Flexible Modeling of Multivariate Count Data via the Multivariate Conway-Maxwell-Poisson Distribution
Description:

This package provides a toolkit containing statistical analysis models motivated by multivariate forms of the Conway-Maxwell-Poisson (COM-Poisson) distribution for flexible modeling of multivariate count data, especially in the presence of data dispersion. Currently the package only supports bivariate data, via the bivariate COM-Poisson distribution described in Sellers et al. (2016) <doi:10.1016/j.jmva.2016.04.007>. Future development will extend the package to higher-dimensional data.

r-mlwrap 0.3.0
Propagated dependencies: r-yardstick@1.3.2 r-workflows@1.3.0 r-tune@2.0.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-sensitivity@1.30.2 r-scales@1.4.0 r-rsample@1.3.1 r-rlang@1.1.6 r-recipes@1.3.1 r-r6@2.6.1 r-patchwork@1.3.2 r-parsnip@1.3.3 r-magrittr@2.0.4 r-innsight@0.3.2 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggbeeswarm@0.7.2 r-fastshap@0.1.1 r-dplyr@1.1.4 r-dials@1.4.2 r-diagrammer@1.0.11 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/AlbertSesePsy/MLwrap
Licenses: GPL 3
Build system: r
Synopsis: Machine Learning Modelling for Everyone
Description:

This package provides a minimal library specifically designed to make the estimation of Machine Learning (ML) techniques as easy and accessible as possible, particularly within the framework of the Knowledge Discovery in Databases (KDD) process in data mining. The package provides essential tools to structure and execute each stage of a predictive or classification modeling workflow, aligning closely with the fundamental steps of the KDD methodology, from data selection and preparation, through model building and tuning, to the interpretation and evaluation of results using Sensitivity Analysis. The MLwrap workflow is organized into four core steps; preprocessing(), build_model(), fine_tuning(), and sensitivity_analysis(). It also includes global and pairwise interaction analysis based on Friedmanâ s H-statistic to support a more detailed interpretation of complex feature relationships.These steps correspond, respectively, to data preparation and transformation, model construction, hyperparameter optimization, and sensitivity analysis. The user can access comprehensive model evaluation results including fit assessment metrics, plots, predictions, and performance diagnostics for ML models implemented through Neural Networks', Random Forest', XGBoost (Extreme Gradient Boosting), and Support Vector Machines (SVM) algorithms. By streamlining these phases, MLwrap aims to simplify the implementation of ML techniques, allowing analysts and data scientists to focus on extracting actionable insights and meaningful patterns from large datasets, in line with the objectives of the KDD process.

r-metasem 1.5.0
Propagated dependencies: r-openmx@2.22.10 r-numderiv@2016.8-1.1 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-mass@7.3-65 r-lavaan@0.6-20 r-ellipse@0.5.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mikewlcheung/metasem
Licenses: GPL 2+
Build system: r
Synopsis: Meta-Analysis using Structural Equation Modeling
Description:

This package provides a collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the OpenMx and lavaan packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices, see Cheung (2015) <doi:10.3389/fpsyg.2014.01521>.

r-metaheuristicopt 2.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=metaheuristicOpt
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Metaheuristic for Optimization
Description:

An implementation of metaheuristic algorithms for continuous optimization. Currently, the package contains the implementations of 21 algorithms, as follows: particle swarm optimization (Kennedy and Eberhart, 1995), ant lion optimizer (Mirjalili, 2015 <doi:10.1016/j.advengsoft.2015.01.010>), grey wolf optimizer (Mirjalili et al., 2014 <doi:10.1016/j.advengsoft.2013.12.007>), dragonfly algorithm (Mirjalili, 2015 <doi:10.1007/s00521-015-1920-1>), firefly algorithm (Yang, 2009 <doi:10.1007/978-3-642-04944-6_14>), genetic algorithm (Holland, 1992, ISBN:978-0262581110), grasshopper optimisation algorithm (Saremi et al., 2017 <doi:10.1016/j.advengsoft.2017.01.004>), harmony search algorithm (Mahdavi et al., 2007 <doi:10.1016/j.amc.2006.11.033>), moth flame optimizer (Mirjalili, 2015 <doi:10.1016/j.knosys.2015.07.006>, sine cosine algorithm (Mirjalili, 2016 <doi:10.1016/j.knosys.2015.12.022>), whale optimization algorithm (Mirjalili and Lewis, 2016 <doi:10.1016/j.advengsoft.2016.01.008>), clonal selection algorithm (Castro, 2002 <doi:10.1109/TEVC.2002.1011539>), differential evolution (Das & Suganthan, 2011), shuffled frog leaping (Eusuff, Landsey & Pasha, 2006), cat swarm optimization (Chu et al., 2006), artificial bee colony algorithm (Karaboga & Akay, 2009), krill-herd algorithm (Gandomi & Alavi, 2012), cuckoo search (Yang & Deb, 2009), bat algorithm (Yang, 2012), gravitational based search (Rashedi et al., 2009) and black hole optimization (Hatamlou, 2013).

r-multiway 1.0-7
Propagated dependencies: r-cmls@1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multiway
Licenses: GPL 2+
Build system: r
Synopsis: Component Models for Multi-Way Data
Description:

Fits multi-way component models via alternating least squares algorithms with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.

r-mmirestriktor 0.3.1
Propagated dependencies: r-shinythemes@1.2.0 r-shiny@1.11.1 r-rpostgres@1.4.8 r-restriktor@0.6-30 r-pool@1.0.4 r-mmcards@0.1.1 r-mass@7.3-65 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mightymetrika/mmirestriktor
Licenses: Expat
Build system: r
Synopsis: Informative Hypothesis Testing Web Applications
Description:

Offering enhanced statistical power compared to traditional hypothesis testing methods, informative hypothesis testing allows researchers to explicitly model their expectations regarding the relationships among parameters. An important software tool for this framework is restriktor'. The mmirestriktor package provides shiny web applications to implement some of the basic functionality of restriktor'. The mmirestriktor() function launches a shiny application for fitting and analyzing models with constraints. The FbarCards() function launches a card game application which can help build intuition about informative hypothesis testing. The iht_interpreter() helps interpret informative hypothesis testing results based on guidelines in Vanbrabant and Rosseel (2020) <doi:10.4324/9780429273872-14>.

r-mecfda 0.2.1
Propagated dependencies: r-refund@0.1-38 r-quantreg@6.1 r-pracma@2.4.6 r-nlme@3.1-168 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-lme4@1.1-37 r-gss@2.2-10 r-glme@0.1.0 r-fda@6.3.0 r-dplyr@1.1.4 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MECfda
Licenses: GPL 3
Build system: r
Synopsis: Scalar-on-Function Regression with Measurement Error Correction
Description:

Solve scalar-on-function linear models, including generalized linear mixed effect model and quantile linear regression model, and bias correction estimation methods due to measurement error. Details about the measurement error bias correction methods, see Luan et al. (2023) <doi:10.48550/arXiv.2305.12624>, Tekwe et al. (2022) <doi:10.1093/biostatistics/kxac017>, Zhang et al. (2023) <doi:10.5705/ss.202021.0246>, Tekwe et al. (2019) <doi:10.1002/sim.8179>.

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