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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-mixedindtests 1.2.0
Propagated dependencies: r-survey@4.4-8 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-copula@1.1-6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MixedIndTests
Licenses: GPL 3
Build system: r
Synopsis: Tests of Randomness and Tests of Independence
Description:

This package provides functions for testing randomness for a univariate time series with arbitrary distribution (discrete, continuous, mixture of both types) and for testing independence between random variables with arbitrary distributions. The test statistics are based on the multilinear empirical copula and multipliers are used to compute P-values. The test of independence between random variables appeared in Genest, Nešlehová, Rémillard & Murphy (2019) and the test of randomness appeared in Nasri (2022).

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-mmpp 0.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mmpp
Licenses: GPL 2
Build system: r
Synopsis: Various Similarity and Distance Metrics for Marked Point Processes
Description:

Compute similarities and distances between marked point processes.

r-minimeta 0.3.2
Propagated dependencies: r-writexls@6.8.0 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-rhandsontable@0.3.8 r-readxl@1.4.5 r-metafor@4.8-0 r-meta@8.2-1 r-markdown@2.0 r-jsonlite@2.0.0 r-colourpicker@1.3.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/thlytras/miniMeta
Licenses: GPL 2+
Build system: r
Synopsis: Web Application to Run Meta-Analyses
Description:

Shiny web application to run meta-analyses. Essentially a graphical front-end to package meta for R. Can be useful as an educational tool, and for quickly analyzing and sharing meta-analyses. Provides output to quickly fill in GRADE (Grading of Recommendations, Assessment, Development and Evaluations) Summary-of-Findings tables. Importantly, it allows further processing of the results inside R, in case more specific analyses are needed.

r-miceranger 1.5.0
Propagated dependencies: r-ranger@0.17.0 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-foreach@1.5.2 r-fnn@1.1.4.1 r-desctools@0.99.60 r-data-table@1.17.8 r-crayon@1.5.3 r-corrplot@0.95
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/FarrellDay/miceRanger
Licenses: Expat
Build system: r
Synopsis: Multiple Imputation by Chained Equations with Random Forests
Description:

Multiple Imputation has been shown to be a flexible method to impute missing values by Van Buuren (2007) <doi:10.1177/0962280206074463>. Expanding on this, random forests have been shown to be an accurate model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing values in datasets. They have the added benefits of returning out of bag error and variable importance estimates, as well as being simple to run in parallel.

r-mrct 0.0.1.0
Propagated dependencies: r-robustbase@0.99-6 r-reshape2@1.4.5 r-rdpack@2.6.4 r-ggplot2@4.0.1 r-fdapace@0.6.0 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mrct
Licenses: GPL 2+
Build system: r
Synopsis: Outlier Detection of Functional Data Based on the Minimum Regularized Covariance Trace Estimator
Description:

Detect outlying observations in functional data sets based on the minimum regularized covariance trace (MRCT) estimator. Includes implementation of Oguamalam et al. (2023) <arXiv:2307.13509>.

r-msip 1.3.7
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-ranger@0.17.0 r-prroc@1.4 r-proc@1.19.0.1 r-plyr@1.8.9 r-mice@3.18.0 r-magrittr@2.0.4 r-e1071@1.7-16 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://cran.r-project.org/package=MSiP
Licenses: GPL 3
Build system: r
Synopsis: 'MassSpectrometry' Interaction Prediction
Description:

The MSiP is a computational approach to predict protein-protein interactions from large-scale affinity purification mass spectrometry (AP-MS) data. This approach includes both spoke and matrix models for interpreting AP-MS data in a network context. The "spoke" model considers only bait-prey interactions, whereas the "matrix" model assumes that each of the identified proteins (baits and prey) in a given AP-MS experiment interacts with each of the others. The spoke model has a high false-negative rate, whereas the matrix model has a high false-positive rate. Although, both statistical models have merits, a combination of both models has shown to increase the performance of machine learning classifiers in terms of their capabilities in discrimination between true and false positive interactions.

r-multilcirt 2.12
Propagated dependencies: r-mass@7.3-65 r-limsolve@2.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiLCIRT
Licenses: GPL 2+
Build system: r
Synopsis: Multidimensional Latent Class Item Response Theory Models
Description:

Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parameterizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version (since 2.1).

r-midasml 0.1.11
Propagated dependencies: r-snow@0.4-4 r-randtoolbox@2.0.5 r-matrix@1.7-4 r-lubridate@1.9.4 r-foreach@1.5.2 r-dorng@1.8.6.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=midasml
Licenses: GPL 2+
Build system: r
Synopsis: Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data
Description:

The midasml package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the midasml approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.

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-mod09nrt 0.14
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mod09nrt
Licenses: GPL 2+
Build system: r
Synopsis: Extraction of Bands from MODIS Surface Reflectance Product MOD09 NRT
Description:

Package for processing downloaded MODIS Surface reflectance Product HDF files. Specifically, MOD09 surface reflectance product files, and the associated MOD03 geolocation files (for MODIS-TERRA). The package will be most effective if the user installs MRTSwath (MODIS Reprojection Tool for swath products; <https://lpdaac.usgs.gov/tools/modis_reprojection_tool_swath>, and adds the directory with the MRTSwath executable to the default R PATH by editing ~/.Rprofile.

r-mvprobit 0.1-10
Propagated dependencies: r-mvtnorm@1.3-3 r-misctools@0.6-28 r-maxlik@1.5-2.1 r-bayesm@3.1-7 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://www.sampleSelection.org
Licenses: GPL 2+
Build system: r
Synopsis: Multivariate Probit Models
Description:

This package provides tools for estimating multivariate probit models, calculating conditional and unconditional expectations, and calculating marginal effects on conditional and unconditional expectations.

r-myclim 1.5.1
Propagated dependencies: r-zoo@1.8-14 r-vroom@1.6.6 r-viridis@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-purrr@1.2.0 r-progress@1.2.3 r-plotly@4.11.0 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-ggforce@0.5.0 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: http://labgis.ibot.cas.cz/myclim/index.html
Licenses: GPL 2+
Build system: r
Synopsis: Microclimatic Data Processing
Description:

Handling the microclimatic data in R. The myClim workflow begins at the reading data primary from microclimatic dataloggers, but can be also reading of meteorological station data from files. Cleaning time step, time zone settings and metadata collecting is the next step of the work flow. With myClim tools one can crop, join, downscale, and convert microclimatic data formats, sort them into localities, request descriptive characteristics and compute microclimatic variables. Handy plotting functions are provided with smart defaults.

r-metalik 0.44.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=metaLik
Licenses: GPL 2+
Build system: r
Synopsis: Likelihood Inference in Meta-Analysis and Meta-Regression Models
Description:

First- and higher-order likelihood inference in meta-analysis and meta-regression models.

r-mnarclust 1.1.0
Propagated dependencies: r-sn@2.1.1 r-rmutil@1.1.10 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://arxiv.org/abs/2009.07662
Licenses: GPL 2+
Build system: r
Synopsis: Clustering Data with Non-Ignorable Missingness using Semi-Parametric Mixture Models
Description:

Clustering of data under a non-ignorable missingness mechanism. Clustering is achieved by a semi-parametric mixture model and missingness is managed by using the pattern-mixture approach. More details of the approach are available in Du Roy de Chaumaray et al. (2020) <arXiv:2009.07662>.

r-minired 1.0.1
Propagated dependencies: r-cpp11@0.5.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=minired
Licenses: GPL 3+
Build system: r
Synopsis: R Interface to 'Redatam' Library
Description:

This package is deprecated. Please use redatamx instead. Provides an API to work with Redatam (see <https://redatam.org>) databases in both formats: RXDB (new format) and DICX (old format) and running Redatam programs written in SPC language. It's a wrapper around Redatam core and provides functions to open/close a database (redatam_open()/redatam_close()), list entities and variables from the database (redatam_entities(), redatam_variables()) and execute a SPC program and gets the results as data frames (redatam_query(), redatam_run()).

r-modalclust 0.7
Propagated dependencies: r-zoo@1.8-14 r-mvtnorm@1.3-3 r-class@7.3-23
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=Modalclust
Licenses: GPL 2
Build system: r
Synopsis: Hierarchical Modal Clustering
Description:

This package performs Modal Clustering (MAC) including Hierarchical Modal Clustering (HMAC) along with their parallel implementation (PHMAC) over several processors. These model-based non-parametric clustering techniques can extract clusters in very high dimensions with arbitrary density shapes. By default clustering is performed over several resolutions and the results are summarised as a hierarchical tree. Associated plot functions are also provided. There is a package vignette that provides many examples. This version adheres to CRAN policy of not spanning more than two child processes by default.

r-mci 1.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MCI
Licenses: GPL 2+
Build system: r
Synopsis: Multiplicative Competitive Interaction (MCI) Model
Description:

Market area models are used to analyze and predict store choices and market areas concerning retail and service locations. This package implements two market area models (Huff Model, Multiplicative Competitive Interaction Model) into R, while the emphases lie on 1.) fitting these models based on empirical data via OLS regression and nonlinear techniques and 2.) data preparation and processing (esp. interaction matrices and data preparation for the MCI Model).

r-mlfdr 0.1.0
Propagated dependencies: r-nmof@2.11-0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MLFDR
Licenses: GPL 2
Build system: r
Synopsis: High Dimensional Mediation Analysis using Local False Discovery Rates
Description:

This package implements a high dimensional mediation analysis algorithm using Local False Discovery Rates. The methodology is described in Roy and Zhang (2024) <doi:10.48550/arXiv.2402.13933>.

r-morphomap 1.5
Propagated dependencies: r-sp@2.2-0 r-rvcg@0.25 r-rgl@1.3.31 r-oce@1.8-3 r-morpho@2.13 r-mgcv@1.9-4 r-lattice@0.22-7 r-geometry@0.5.2 r-desctools@0.99.60 r-colorramps@2.3.4 r-arothron@2.0.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=morphomap
Licenses: GPL 2
Build system: r
Synopsis: Morphometric Maps, Bone Landmarking and Cross Sectional Geometry
Description:

Extract cross sections from long bone meshes at specified intervals along the diaphysis. Calculate two and three-dimensional morphometric maps, cross-sectional geometric parameters, and semilandmarks on the periosteal and endosteal contours of each cross section.

r-microsynth 2.0.51
Propagated dependencies: r-survey@4.4-8 r-pracma@2.4.6 r-lowrankqp@1.0.6 r-kernlab@0.9-33
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=microsynth
Licenses: GPL 3
Build system: r
Synopsis: Synthetic Control Methods with Micro- And Meso-Level Data
Description:

This package provides a generalization of the Synth package that is designed for data at a more granular level (e.g., micro-level). Provides functions to construct weights (including propensity score-type weights) and run analyses for synthetic control methods with micro- and meso-level data; see Robbins, Saunders, and Kilmer (2017) <doi:10.1080/01621459.2016.1213634> and Robbins and Davenport (2021) <doi:10.18637/jss.v097.i02>.

r-mqmf 0.1.5
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/haddonm/MQMF/
Licenses: GPL 3
Build system: r
Synopsis: Modelling and Quantitative Methods in Fisheries
Description:

Complements the book "Using R for Modelling and Quantitative Methods in Fisheries" ISBN 9780367469894, published in 2021 by Chapman & Hall in their "Using R series". There are numerous functions and data-sets that are used in the book's many practical examples.

r-mscquartets 3.2
Propagated dependencies: r-zipfr@0.6-70 r-rdpack@2.6.4 r-rcppprogress@0.4.2 r-rcpp@1.1.0 r-phangorn@2.12.1 r-igraph@2.2.1 r-foreach@1.5.2 r-doparallel@1.0.17 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=MSCquartets
Licenses: Expat
Build system: r
Synopsis: Analyzing Gene Tree Quartets under the Multi-Species Coalescent
Description:

This package provides methods for analyzing and using quartets displayed on a collection of gene trees, primarily to make inferences about the species tree or network under the multi-species coalescent model. These include quartet hypothesis tests for the model, as developed by Mitchell et al. (2019) <doi:10.1214/19-EJS1576>, simplex plots of quartet concordance factors as presented by Allman et al. (2020) <doi:10.1101/2020.02.13.948083>, species tree inference methods based on quartet distances of Rhodes (2019) <doi:10.1109/TCBB.2019.2917204> and Yourdkhani and Rhodes (2019) <doi:10.1007/s11538-020-00773-4>, the NANUQ algorithm for inference of level-1 species networks of Allman et al. (2019) <doi:10.1186/s13015-019-0159-2>, the TINNIK algorithm for inference of the tree of blobs of an arbitrary network of Allman et al.(2022) <doi:10.1007/s00285-022-01838-9>, and NANUQ+ routines for resolving multifurcations in the tree of blobs to cycles as in Allman et al.(2024) (forthcoming). Software announcement by Rhodes et al. (2020) <doi:10.1093/bioinformatics/btaa868>.

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.

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