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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-mapmisc 2.1.3
Propagated dependencies: r-terra@1.8-86 r-geosphere@1.5-20
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mapmisc
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Utilities for Producing Maps
Description:

This package provides a minimal, light-weight set of tools for producing nice looking maps in R, with support for map projections. See Brown (2016) <doi:10.32614/RJ-2016-005>.

r-mhtdiscrete 1.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://allen.shinyapps.io/MTPs/
Licenses: GPL 2+
Build system: r
Synopsis: Multiple Hypotheses Testing for Discrete Data
Description:

This package provides a comprehensive tool for almost all existing multiple testing methods for discrete data. The package also provides some novel multiple testing procedures controlling FWER/FDR for discrete data. Given discrete p-values and their domains, the [method].p.adjust function returns adjusted p-values, which can be used to compare with the nominal significant level alpha and make decisions. For users convenience, the functions also provide the output option for printing decision rules.

r-mosaiccalc 0.6.4
Propagated dependencies: r-tibble@3.3.0 r-sp@2.2-0 r-ryacas@1.1.6 r-rlang@1.1.6 r-orthopolynom@1.0-6.1 r-mosaiccore@0.9.5 r-mosaic@1.9.2 r-metr@0.18.3 r-matrix@1.7-4 r-mass@7.3-65 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggformula@1.0.0 r-dplyr@1.1.4 r-deriv@4.2.0 r-calculus@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/ProjectMOSAIC/mosaicCalc
Licenses: GPL 2+
Build system: r
Synopsis: R-Language Based Calculus Operations for Teaching
Description:

Software to support the introductory *MOSAIC Calculus* textbook <https://www.mosaic-web.org/MOSAIC-Calculus/>), one of many data- and modeling-oriented educational resources developed by Project MOSAIC (<https://www.mosaic-web.org/>). Provides symbolic and numerical differentiation and integration, as well as support for applied linear algebra (for data science), and differential equations/dynamics. Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc. The software is suitable for general use, but intended mainly for teaching calculus.

r-mase 0.1.5.2
Propagated dependencies: r-tidyr@1.3.1 r-survey@4.4-8 r-rpms@0.5.1 r-rdpack@2.6.4 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-glmnet@4.1-10 r-ellipsis@0.3.2 r-dplyr@1.1.4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mase
Licenses: GPL 2
Build system: r
Synopsis: Model-Assisted Survey Estimators
Description:

This package provides a set of model-assisted survey estimators and corresponding variance estimators for single stage, unequal probability, without replacement sampling designs. All of the estimators can be written as a generalized regression estimator with the Horvitz-Thompson, ratio, post-stratified, and regression estimators summarized by Sarndal et al. (1992, ISBN:978-0-387-40620-6). Two of the estimators employ a statistical learning model as the assisting model: the elastic net regression estimator, which is an extension of the lasso regression estimator given by McConville et al. (2017) <doi:10.1093/jssam/smw041>, and the regression tree estimator described in McConville and Toth (2017) <arXiv:1712.05708>. The variance estimators which approximate the joint inclusion probabilities can be found in Berger and Tille (2009) <doi:10.1016/S0169-7161(08)00002-3> and the bootstrap variance estimator is presented in Mashreghi et al. (2016) <doi:10.1214/16-SS113>.

r-meteospain 0.3.1
Propagated dependencies: r-xml2@1.5.0 r-vctrs@0.6.5 r-units@1.0-0 r-tidyr@1.3.1 r-stringr@1.6.0 r-sf@1.0-23 r-rvest@1.0.5 r-rlang@1.1.6 r-purrr@1.2.0 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr2@1.2.1 r-glue@1.8.0 r-dplyr@1.1.4 r-cli@3.6.5 r-cachem@1.1.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://emf-creaf.github.io/meteospain/
Licenses: Expat
Build system: r
Synopsis: Access to Spanish Meteorological Stations Services
Description:

Access to different Spanish meteorological stations data services and APIs (AEMET, SMC, MG, Meteoclimatic...).

r-mmem 0.1.1
Propagated dependencies: r-stringr@1.6.0 r-psych@2.5.6 r-matrixcalc@1.0-6 r-matrix@1.7-4 r-mass@7.3-65 r-lme4@1.1-37 r-jointdiag@0.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MMeM
Licenses: GPL 3
Build system: r
Synopsis: Multivariate Mixed Effects Model
Description:

Analyzing data under multivariate mixed effects model using multivariate REML and multivariate Henderson3 methods. See Meyer (1985) <doi:10.2307/2530651> and Wesolowska Janczarek (1984) <doi:10.1002/bimj.4710260613>.

r-mtlgmm 0.1.0
Propagated dependencies: r-mclust@6.1.2 r-foreach@1.5.2 r-doparallel@1.0.17 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=mtlgmm
Licenses: GPL 2
Build system: r
Synopsis: Unsupervised Multi-Task and Transfer Learning on Gaussian Mixture Models
Description:

Unsupervised learning has been widely used in many real-world applications. One of the simplest and most important unsupervised learning models is the Gaussian mixture model (GMM). In this work, we study the multi-task learning problem on GMMs, which aims to leverage potentially similar GMM parameter structures among tasks to obtain improved learning performance compared to single-task learning. We propose a multi-task GMM learning procedure based on the Expectation-Maximization (EM) algorithm that not only can effectively utilize unknown similarity between related tasks but is also robust against a fraction of outlier tasks from arbitrary sources. The proposed procedure is shown to achieve minimax optimal rate of convergence for both parameter estimation error and the excess mis-clustering error, in a wide range of regimes. Moreover, we generalize our approach to tackle the problem of transfer learning for GMMs, where similar theoretical results are derived. Finally, we demonstrate the effectiveness of our methods through simulations and a real data analysis. To the best of our knowledge, this is the first work studying multi-task and transfer learning on GMMs with theoretical guarantees. This package implements the algorithms proposed in Tian, Y., Weng, H., & Feng, Y. (2022) <arXiv:2209.15224>.

r-manlymix 0.1.15.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=ManlyMix
Licenses: GPL 2+
Build system: r
Synopsis: Manly Mixture Modeling and Model-Based Clustering
Description:

The utility of this package includes finite mixture modeling and model-based clustering through Manly mixture models by Zhu and Melnykov (2016) <DOI:10.1016/j.csda.2016.01.015>. It also provides capabilities for forward and backward model selection procedures.

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-matlabr 1.5.2
Propagated dependencies: r-stringr@1.6.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=matlabr
Licenses: GPL 2
Build system: r
Synopsis: An Interface for MATLAB using System Calls
Description:

This package provides users to call MATLAB from using the "system" command. Allows users to submit lines of code or MATLAB m files. This is in comparison to R.matlab', which creates a MATLAB server.

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-mdma 2.0.0
Propagated dependencies: r-performance@0.15.2 r-mass@7.3-65 r-lme4@1.1-37 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mathijsdeen/MDMA
Licenses: GPL 3
Build system: r
Synopsis: Mathijs Deen's Miscellaneous Auxiliaries
Description:

This package provides a variety of functions useful for data analysis, selection, manipulation, and graphics.

r-modeler 3.4.9
Propagated dependencies: r-tailrank@3.2.4 r-rpart@4.1.24 r-randomforest@4.7-1.2 r-oompabase@3.2.10 r-nnet@7.3-20 r-neuralnet@1.44.2 r-e1071@1.7-16 r-classdiscovery@3.4.9 r-classcomparison@3.3.5 r-class@7.3-23
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://oompa.r-forge.r-project.org/
Licenses: ASL 2.0
Build system: r
Synopsis: Classes and Methods for Training and Using Binary Prediction Models
Description:

Defines classes and methods to learn models and use them to predict binary outcomes. These are generic tools, but we also include specific examples for many common classifiers.

r-metarep 1.2.1
Propagated dependencies: r-meta@8.2-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/IJaljuli/metarep
Licenses: GPL 2+
Build system: r
Synopsis: Replicability-Analysis Tools for Meta-Analysis
Description:

User-friendly package for reporting replicability-analysis methods, affixed to meta-analyses summary. The replicability-analysis output provides an assessment of the investigated intervention, where it offers quantification of effect replicability and assessment of the consistency of findings. - Replicability-analysis for fixed-effects and random-effect meta analysis: - r(u)-value; - lower bounds on the number of studies with replicated positive and\or negative effect; - Allows detecting inconsistency of signals; - forest plots with the summary of replicability analysis results; - Allows Replicability-analysis with or without the common-effect assumption.

r-misaem 1.1.0
Propagated dependencies: r-norm@1.0-11.1 r-mvtnorm@1.3-3 r-mass@7.3-65 r-glmnet@4.1-10 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/julierennes/misaem
Licenses: GPL 3
Build system: r
Synopsis: Linear Regression and Logistic Regression with Missing Covariates
Description:

Estimate parameters of linear regression and logistic regression with missing covariates with missing data, perform model selection and prediction, using EM-type algorithms. Jiang W., Josse J., Lavielle M., TraumaBase Group (2020) <doi:10.1016/j.csda.2019.106907>.

r-mbres 0.1.7
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-scales@1.4.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mbRes
Licenses: GPL 3
Build system: r
Synopsis: Exploration of Multiple Biomarker Responses using Effect Size
Description:

Summarize multiple biomarker responses of aquatic organisms to contaminants using Cliffâ s delta, as described in Pham & Sokolova (2023) <doi:10.1002/ieam.4676>.

r-multgee 1.9.0
Propagated dependencies: r-vgam@1.1-13 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-gnm@1.1-5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/AnestisTouloumis/multgee
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: GEE Solver for Correlated Nominal or Ordinal Multinomial Responses
Description:

GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parameterization.

r-metevalue 0.2.4
Propagated dependencies: r-sqldf@0.4-11 r-psych@2.5.6 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=metevalue
Licenses: FSDG-compatible
Build system: r
Synopsis: E-Value in the Omics Data Association Studies
Description:

In the omics data association studies, it is common to conduct the p-value corrections to control the false significance. Beyond the P-value corrections, E-value is recently studied to facilitate multiple testing correction based on V. Vovk and R. Wang (2021) <doi:10.1214/20-AOS2020>. This package provides E-value calculation for DNA methylation data and RNA-seq data. Currently, five data formats are supported: DNA methylation levels using DMR detection tools (BiSeq, DMRfinder, MethylKit, Metilene and other DNA methylation tools) and RNA-seq data. The relevant references are listed below: Katja Hebestreit and Hans-Ulrich Klein (2022) <doi:10.18129/B9.bioc.BiSeq>; Altuna Akalin et.al (2012) <doi:10.18129/B9.bioc.methylKit>.

r-memify 0.1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=memify
Licenses: GPL 3
Build system: r
Synopsis: Constructing Functions That Keep State
Description:

This package provides a simple way to construct and maintain functions that keep state i.e. remember their argument lists. This can be useful when one needs to repeatedly invoke the same function with only a small number of argument changes at each invocation.

r-mmcsd 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlist@0.4.6.2 r-purrr@1.2.0 r-magrittr@2.0.4 r-knitr@1.50 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=Mmcsd
Licenses: GPL 3+
Build system: r
Synopsis: Modeling Complex Longitudinal Data in a Quick and Easy Way
Description:

Matching longitudinal methodology models with complex sampling design. It fits fixed and random effects models and covariance structured models so far. It also provides tools to perform statistical tests considering these specifications as described in : Pacheco, P. H. (2021). "Modeling complex longitudinal data in R: development of a statistical package." <https://repositorio.ufjf.br/jspui/bitstream/ufjf/13437/1/pedrohenriquedemesquitapacheco.pdf>.

r-metabodecon 1.6.2
Propagated dependencies: r-withr@3.0.2 r-toscutil@2.8.0 r-speaq@2.7.0 r-readjdx@0.6.4 r-mathjaxr@1.8-0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/spang-lab/metabodecon/
Licenses: GPL 3+
Build system: r
Synopsis: Deconvolution and Alignment of 1d NMR Spectra
Description:

This package provides a framework for deconvolution, alignment and postprocessing of 1-dimensional (1d) nuclear magnetic resonance (NMR) spectra, resulting in a data matrix of aligned signal integrals. The deconvolution part uses the algorithm described in Koh et al. (2009) <doi:10.1016/j.jmr.2009.09.003>. The alignment part is based on functions from the speaq package, described in Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018> and Vu et al. (2011) <doi:10.1186/1471-2105-12-405>. A detailed description and evaluation of an early version of the package, MetaboDecon1D v0.2.2', can be found in Haeckl et al. (2021) <doi:10.3390/metabo11070452>.

r-mcvis 1.0.8
Propagated dependencies: r-shiny@1.11.1 r-rlang@1.1.6 r-reshape2@1.4.5 r-purrr@1.2.0 r-psych@2.5.6 r-magrittr@2.0.4 r-igraph@2.2.1 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mcvis
Licenses: GPL 3
Build system: r
Synopsis: Multi-Collinearity Visualization
Description:

Visualize the relationship between linear regression variables and causes of multi-collinearity. Implements the method in Lin et. al. (2020) <doi:10.1080/10618600.2020.1779729>.

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-missmethods 0.4.0
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/torockel/missMethods
Licenses: GPL 3
Build system: r
Synopsis: Methods for Missing Data
Description:

Supply functions for the creation and handling of missing data as well as tools to evaluate missing data methods. Nearly all possibilities of generating missing data discussed by Santos et al. (2019) <doi:10.1109/ACCESS.2019.2891360> and some additional are implemented. Functions are supplied to compare parameter estimates and imputed values to true values to evaluate missing data methods. Evaluations of these types are done, for example, by Cetin-Berber et al. (2019) <doi:10.1177/0013164418805532> and Kim et al. (2005) <doi:10.1093/bioinformatics/bth499>.

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