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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-meteo 2.0-3
Propagated dependencies: r-units@1.0-0 r-terra@1.8-86 r-spacetime@1.3-3 r-sp@2.2-0 r-snowfall@1.84-6.3 r-sftime@0.3.1 r-sf@1.0-23 r-raster@3.6-32 r-ranger@0.17.0 r-plyr@1.8.9 r-nabor@0.5.0 r-jsonlite@2.0.0 r-gstat@2.1-4 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-desctools@0.99.60 r-data-table@1.17.8 r-cast@1.0.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.r-pkg.org/pkg/meteo
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: RFSI & STRK Interpolation for Meteo and Environmental Variables
Description:

Random Forest Spatial Interpolation (RFSI, SekuliÄ et al. (2020) <doi:10.3390/rs12101687>) and spatio-temporal geostatistical (spatio-temporal regression Kriging (STRK)) interpolation for meteorological (Kilibarda et al. (2014) <doi:10.1002/2013JD020803>, SekuliÄ et al. (2020) <doi:10.1007/s00704-019-03077-3>) and other environmental variables. Contains global spatio-temporal models calculated using publicly available data.

r-mflica 0.1.7
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/DarkEyes/mFLICA
Licenses: GPL 3
Build system: r
Synopsis: Leadership-Inference Framework for Multivariate Time Series
Description:

This package provides a leadership-inference framework for multivariate time series. The framework for multiple-faction-leadership inference from coordinated activities or mFLICA uses a notion of a leader as an individual who initiates collective patterns that everyone in a group follows. Given a set of time series of individual activities, our goal is to identify periods of coordinated activity, find factions of coordination if more than one exist, as well as identify leaders of each faction. For each time step, the framework infers following relations between individual time series, then identifying a leader of each faction whom many individuals follow but it follows no one. A faction is defined as a group of individuals that everyone follows the same leader. mFLICA reports following relations, leaders of factions, and members of each faction for each time step. Please see Chainarong Amornbunchornvej and Tanya Berger-Wolf (2018) <doi:10.1137/1.9781611975321.62> for methodology and Chainarong Amornbunchornvej (2021) <doi:10.1016/j.softx.2021.100781> for software when referring to this package in publications.

r-mpower 0.1.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-snow@0.4-4 r-sbgcop@1.0 r-rlang@1.1.6 r-reshape2@1.4.5 r-purrr@1.2.0 r-mass@7.3-65 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-dosnow@1.0.20 r-boot@1.3-32 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mpower
Licenses: LGPL 2.0+
Build system: r
Synopsis: Power Analysis via Monte Carlo Simulation for Correlated Data
Description:

This package provides a flexible framework for power analysis using Monte Carlo simulation for settings in which considerations of the correlations between predictors are important. Users can set up a data generative model that preserves dependence structures among predictors given existing data (continuous, binary, or ordinal). Users can also generate power curves to assess the trade-offs between sample size, effect size, and power of a design. This package includes several statistical models common in environmental mixtures studies. For more details and tutorials, see Nguyen et al. (2022) <arXiv:2209.08036>.

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-mwa 0.5.1
Dependencies: openjdk@25
Propagated dependencies: r-rjava@1.0-11 r-mass@7.3-65 r-cem@1.1.31
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mwa
Licenses: LGPL 3
Build system: r
Synopsis: Causal Inference in Spatiotemporal Event Data
Description:

Implementation of Matched Wake Analysis (mwa) for studying causal relationships in spatiotemporal event data, introduced by Schutte and Donnay (2014) <doi:10.1016/j.polgeo.2014.03.001>.

r-minimax 1.1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=minimax
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: The Minimax Distribution Family
Description:

The minimax family of distributions is a two-parameter family like the beta family, but computationally a lot more tractible.

r-mixgb 2.2.3
Propagated dependencies: r-xgboost@1.7.11.1 r-rfast@2.1.5.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mice@3.18.0 r-matrix@1.7-4 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/agnesdeng/mixgb
Licenses: GPL 3+
Build system: r
Synopsis: Multiple Imputation Through 'XGBoost'
Description:

Multiple imputation using XGBoost', subsampling, and predictive mean matching as described in Deng and Lumley (2024) <doi:10.1080/10618600.2023.2252501>. The package supports various types of variables, offers flexible settings, and enables saving an imputation model to impute new data. Data processing and memory usage have been optimised to speed up the imputation process.

r-mplustrees 0.2.3
Propagated dependencies: r-rpart-plot@3.1.4 r-rpart@4.1.24 r-nlme@3.1-168 r-mplusautomation@1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MplusTrees
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Decision Trees with Structural Equation Models Fit in 'Mplus'
Description:

Uses recursive partitioning to create homogeneous subgroups based on structural equation models fit in Mplus', a stand-alone program developed by Muthen and Muthen.

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-mxsem 0.1.0
Propagated dependencies: r-rcpp@1.1.0 r-openmx@2.22.10 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://jhorzek.github.io/mxsem/
Licenses: GPL 3+
Build system: r
Synopsis: Specify 'OpenMx' Models with a 'lavaan'-Style Syntax
Description:

This package provides a lavaan'-like syntax for OpenMx models. The syntax supports definition variables, bounds, and parameter transformations. This allows for latent growth curve models with person-specific measurement occasions, moderated nonlinear factor analysis and much more.

r-mdhglm 1.8
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 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=mdhglm
Licenses: FSDG-compatible
Build system: r
Synopsis: Multivariate Double Hierarchical Generalized Linear Models
Description:

Allows various models for multivariate response variables where each response is assumed to follow double hierarchical generalized linear models. In double hierarchical generalized linear models, the mean, dispersion parameters for variance of random effects, and residual variance can be further modeled as random-effect models.

r-monobinshiny 0.1.0
Propagated dependencies: r-shinyjs@2.1.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-monobin@0.2.4 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/andrija-djurovic/monobinShiny
Licenses: GPL 3+
Build system: r
Synopsis: Shiny User Interface for 'monobin' Package
Description:

This is an add-on package to the monobin package that simplifies its use. It provides shiny-based user interface (UI) that is especially handy for less experienced R users as well as for those who intend to perform quick scanning of numeric risk factors when building credit rating models. The additional functions implemented in monobinShiny that do no exist in monobin package are: descriptive statistics, special case and outliers imputation. The function descriptive statistics is exported and can be used in R sessions independently from the user interface, while special case and outlier imputation functions are written to be used with shiny UI.

r-mppr 1.5.0
Propagated dependencies: r-qtl@1.72 r-nlme@3.1-168 r-matrix@1.7-4 r-igraph@2.2.1 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://github.com/vincentgarin/mppR
Licenses: GPL 3
Build system: r
Synopsis: Multi-Parent Population QTL Analysis
Description:

Analysis of experimental multi-parent populations to detect regions of the genome (called quantitative trait loci, QTLs) influencing phenotypic traits measured in unique and multiple environments. The population must be composed of crosses between a set of at least three parents (e.g. factorial design, diallel', or nested association mapping). The functions cover data processing, QTL detection, and results visualization. The implemented methodology is described in Garin, Wimmer, Mezmouk, Malosetti and van Eeuwijk (2017) <doi:10.1007/s00122-017-2923-3>, in Garin, Malosetti and van Eeuwijk (2020) <doi: 10.1007/s00122-020-03621-0>, and in Garin, Diallo, Tekete, Thera, ..., and Rami (2024) <doi: 10.1093/genetics/iyae003>.

r-meddatasets 0.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/lightbluetitan/meddatasets
Licenses: GPL 3
Build system: r
Synopsis: Comprehensive Medical, Disease, Treatment, and Drug Datasets
Description:

This package provides an extensive collection of datasets related to medicine, diseases, treatments, drugs, and public health. This package covers topics such as drug effectiveness, vaccine trials, survival rates, infectious disease outbreaks, and medical treatments. The included datasets span various health conditions, including AIDS, cancer, bacterial infections, and COVID-19, along with information on pharmaceuticals and vaccines. These datasets are sourced from the R ecosystem and other R packages, remaining unaltered to ensure data integrity. This package serves as a valuable resource for researchers, analysts, and healthcare professionals interested in conducting medical and public health data analysis in R.

r-mappp 1.0.0
Propagated dependencies: r-rlang@1.1.6 r-purrr@1.2.0 r-progress@1.2.3 r-pbmcapply@1.5.1 r-parallelly@1.45.1 r-memoise@2.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/cole-brokamp/mappp
Licenses: Expat
Build system: r
Synopsis: Map in Parallel with Progress
Description:

This package provides one function, which is a wrapper around purrr::map() with some extras on top, including parallel computation, progress bars, error handling, and result caching.

r-managedcloudprovider 1.0.0
Propagated dependencies: r-jsonlite@2.0.0 r-dockerparallel@1.0.4 r-adagio@0.9.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/Jiefei-Wang/ManagedCloudProvider
Licenses: GPL 3
Build system: r
Synopsis: Providing the Kubernetes-Like Functions for the Non-Kubernetes Cloud Service
Description:

Providing the kubernetes-like class ManagedCloudProvider as a child class of the CloudProvider class in the DockerParallel package. The class is able to manage the cloud instance made by the non-kubernetes cloud service. For creating a provider for the non-kubernetes cloud service, the developer needs to define a reference class inherited from ManagedCloudProvider and define the method for the generics runDockerWorkerContainers(), getDockerWorkerStatus() and killDockerWorkerContainers(). For more information, please see the vignette in this package and <https://CRAN.R-project.org/package=DockerParallel>.

r-medextractr 0.4.1
Propagated dependencies: r-stringr@1.6.0 r-stringi@1.8.7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=medExtractR
Licenses: GPL 2+
Build system: r
Synopsis: Extraction of Medication Information from Clinical Text
Description:

Function and support for medication and dosing information extraction from free-text clinical notes. Medication entities for the basic medExtractR implementation that can be extracted include drug name, strength, dose amount, dose, frequency, intake time, dose change, and time of last dose. The basic medExtractR is outlined in Weeks, Beck, McNeer, Williams, Bejan, Denny, Choi (2020) <doi: 10.1093/jamia/ocz207>. The extended medExtractR_tapering implementation is intended to extract dosing information for more tapering schedules, which are far more complex. The tapering extension allows for the extraction of additional entities including dispense amount, refills, dose schedule, time keyword, transition, and preposition.

r-multisite-accuracy 1.3
Propagated dependencies: r-survival@3.8-3 r-proc@1.19.0.1 r-metafor@4.8-0 r-logistf@1.26.1 r-lmertest@3.1-3 r-lme4@1.1-37 r-coxme@2.2-22
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multisite.accuracy
Licenses: GPL 3
Build system: r
Synopsis: Estimation of Accuracy in Multisite Machine-Learning Models
Description:

The effects of the site may severely bias the accuracy of a multisite machine-learning model, even if the analysts removed them when fitting the model in the training set and applying the model in the test set (Solanes et al., Neuroimage 2023, 265:119800). This simple R package estimates the accuracy of a multisite machine-learning model unbiasedly, as described in (Solanes et al., Psychiatry Research: Neuroimaging 2021, 314:111313). It currently supports the estimation of sensitivity, specificity, balanced accuracy (for binary or multinomial variables), the area under the curve, correlation, mean squarer error, and hazard ratio for binomial, multinomial, gaussian, and survival (time-to-event) outcomes.

r-mscsimtester 1.1
Propagated dependencies: r-rdpack@2.6.4 r-ksamples@1.2-12 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=MSCsimtester
Licenses: Expat
Build system: r
Synopsis: Tests of Multispecies Coalescent Gene Tree Simulator Output
Description:

Statistical tests for validating multispecies coalescent gene tree simulators, using pairwise distances and rooted triple counts. See Allman ES, Baños HD, Rhodes JA 2023. Testing multispecies coalescent simulators using summary statistics, IEEE/ACM Trans Comput Biol Bioinformat, 20(2):1613â 1618. <doi:10.1109/TCBB.2022.3177956>.

r-mlr3db 0.7.0
Propagated dependencies: r-r6@2.6.1 r-mlr3misc@0.19.0 r-mlr3@1.2.0 r-data-table@1.17.8 r-checkmate@2.3.3 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mlr3db.mlr-org.com
Licenses: LGPL 3
Build system: r
Synopsis: Data Base Backend for 'mlr3'
Description:

Extends the mlr3 package with a backend to transparently work with databases such as SQLite', DuckDB', MySQL', MariaDB', or PostgreSQL'. The package provides three additional backends: DataBackendDplyr relies on the abstraction of package dbplyr to interact with most DBMS. DataBackendDuckDB operates on DuckDB data bases and also on Apache Parquet files. DataBackendPolars operates on Polars data frames.

r-mexicolors 0.2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mexicolors
Licenses: GPL 2+
Build system: r
Synopsis: Mexican Politics-Inspired Color Palette Generator
Description:

This package provides a color palette generator inspired by Mexican politics, with colors ranging from red on the left to gray in the middle and green on the right. Palette options range from only a few colors to several colors, but with discrete and continuous options to offer greatest flexibility to the user. This package allows for a range of applications, from mapping brief discrete scales (e.g., four colors for Morena, PRI, and PAN) to continuous interpolated arrays including dozens of shades graded from red to green.

r-msce 1.0.2
Propagated dependencies: r-rcppparallel@5.1.11-1 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=msce
Licenses: GPL 2+
Build system: r
Synopsis: Hazard of Multi-Stage Clonal Expansion Models
Description:

This package provides functions to calculate hazard and survival function of Multi-Stage Clonal Expansion Models used in cancer epidemiology. For the Two-Stage Clonal Expansion Model an exact solution is implemented assuming piecewise constant parameters, see Heidenreich, Luebeck, Moolgavkar (1997) <doi:10.1111/j.1539-6924.1997.tb00878.x>. Numerical solutions are provided for its extensions, see also Little, Vineis, Li (2008) <doi:10.1016/j.jtbi.2008.05.027>.

r-midi 0.1.0
Propagated dependencies: r-withr@3.0.2 r-rlang@1.1.6 r-r6@2.6.1 r-purrr@1.2.0 r-plotly@4.11.0 r-ggplot2@4.0.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/lmjl-alea/midi
Licenses: Expat
Build system: r
Synopsis: Microstructure Information from Diffusion Imaging
Description:

An implementation of a taxonomy of models of restricted diffusion in biological tissues parametrized by the tissue geometry (axis, diameter, density, etc.). This is primarily used in the context of diffusion magnetic resonance (MR) imaging to model the MR signal attenuation in the presence of diffusion gradients. The goal is to provide tools to simulate the MR signal attenuation predicted by these models under different experimental conditions. The package feeds a companion shiny app available at <https://midi-pastrami.apps.math.cnrs.fr> that serves as a graphical interface to the models and tools provided by the package. Models currently available are the ones in Neuman (1974) <doi:10.1063/1.1680931>, Van Gelderen et al. (1994) <doi:10.1006/jmrb.1994.1038>, Stanisz et al. (1997) <doi:10.1002/mrm.1910370115>, Soderman & Jonsson (1995) <doi:10.1006/jmra.1995.0014> and Callaghan (1995) <doi:10.1006/jmra.1995.1055>.

r-msos 1.2.0
Propagated dependencies: r-tree@1.0-45 r-mclust@6.1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/coatless/msos
Licenses: Expat
Build system: r
Synopsis: Data Sets and Functions Used in Multivariate Statistics: Old School by John Marden
Description:

Multivariate Analysis methods and data sets used in John Marden's book Multivariate Statistics: Old School (2015) <ISBN:978-1456538835>. This also serves as a companion package for the STAT 571: Multivariate Analysis course offered by the Department of Statistics at the University of Illinois at Urbana-Champaign ('UIUC').

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