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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-mlr3summary 0.1.1
Propagated dependencies: r-mlr3misc@0.19.0 r-mlr3@1.2.0 r-future-apply@1.20.0 r-data-table@1.17.8 r-cli@3.6.5 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://cran.r-project.org/package=mlr3summary
Licenses: LGPL 3
Build system: r
Synopsis: Model and Learner Summaries for 'mlr3'
Description:

Concise and interpretable summaries for machine learning models and learners of the mlr3 ecosystem. The package takes inspiration from the summary function for (generalized) linear models but extends it to non-parametric machine learning models, based on generalization performance, model complexity, feature importances and effects, and fairness metrics.

r-mfusampler 1.1.0
Propagated dependencies: r-dlm@1.1-6.1 r-coda@0.19-4.1 r-ars@0.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MfUSampler
Licenses: GPL 2+
Build system: r
Synopsis: Multivariate-from-Univariate (MfU) MCMC Sampler
Description:

Convenience functions for multivariate MCMC using univariate samplers including: slice sampler with stepout and shrinkage (Neal (2003) <DOI:10.1214/aos/1056562461>), adaptive rejection sampler (Gilks and Wild (1992) <DOI:10.2307/2347565>), adaptive rejection Metropolis (Gilks et al (1995) <DOI:10.2307/2986138>), and univariate Metropolis with Gaussian proposal.

r-memshare 1.1.0
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://www.iap-gmbh.de
Licenses: GPL 3
Build system: r
Synopsis: Shared Memory Multithreading
Description:

This project extends R with a mechanism for efficient parallel data access by utilizing C++ shared memory. Large data objects can be accessed and manipulated directly from R without redundant copying, providing both speed and memory efficiency.

r-mosemiind 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-pracma@2.4.6 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=MOsemiind
Licenses: Expat
Build system: r
Synopsis: Marshall-Olkin Shock Models with Semi-Independent Time
Description:

This package provides tools for analyzing Marshall-Olkin shock models semi-independent time. It includes interactive shiny applications for exploring copula-based dependence structures, along with functions for modeling and visualization. The methods are based on Mijanovic and Popovic (2024, submitted) "An R package for Marshall-Olkin shock models with semi-independent times.".

r-maq 0.6.0
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/grf-labs/maq
Licenses: Expat
Build system: r
Synopsis: Multi-Armed Qini
Description:

Policy evaluation using generalized Qini curves: Evaluate data-driven treatment targeting rules for one or more treatment arms over different budget constraints in experimental or observational settings under unconfoundedness.

r-minerva 1.5.10
Propagated dependencies: 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://www.r-project.org
Licenses: GPL 3
Build system: r
Synopsis: Maximal Information-Based Nonparametric Exploration for Variable Analysis
Description:

Wrapper for minepy implementation of Maximal Information-based Nonparametric Exploration statistics (MIC and MINE family). Detailed information of the ANSI C implementation of minepy can be found at <http://minepy.readthedocs.io/en/latest>.

r-mde 0.3.2
Propagated dependencies: r-tidyr@1.3.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/Nelson-Gon/mde
Licenses: GPL 3
Build system: r
Synopsis: Missing Data Explorer
Description:

Correct identification and handling of missing data is one of the most important steps in any analysis. To aid this process, mde provides a very easy to use yet robust framework to quickly get an idea of where the missing data lies and therefore find the most appropriate action to take. Graham WJ (2009) <doi:10.1146/annurev.psych.58.110405.085530>.

r-mtanan 0.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mtanan
Licenses: GPL 3
Build system: r
Synopsis: Single Valued Neutrosophic Kruskal-Wallis and Mann Whitney Tests
Description:

Dealing with neutrosophic data in single valued form using score, accuracy and certainty functions to calculate ranks of Single Valued Neutrosophic Set (SVNS), also to calculate the Mann-Whitney test, and making a post-hoc test after rejecting the null hypothesis using the Neutrosophic Statistics Kruskal-Wallis test. For more information see Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022) <https://digitalrepository.unm.edu/nss_journal/vol51/iss1/60/>.

r-minorparties 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-spacyr@1.3.0 r-rlang@1.1.6 r-reticulate@1.44.1 r-quanteda-textmodels@0.9.10 r-quanteda@4.3.1 r-purrr@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://gerckentheodore.github.io/minorparties/
Licenses: GPL 3+
Build system: r
Synopsis: Quantitatively Analyze Minor Political Parties
Description:

This package provides tools for calculating I-Scores, a simple way to measure how successful minor political parties are at influencing the major parties in their environment. I-Scores are designed to be a more comprehensive measurement of minor party success than vote share and legislative seats won, the current standard measurements, which do not reflect the strategies that most minor parties employ. The procedure leverages the Manifesto Project's NLP model to identify the issue areas that sentences discuss, see Burst et al. (2024) <doi:10.25522/manifesto.manifestoberta.56topics.context.2024.1.1>, and the Wordfish algorithm to estimate the relative positions that platforms take on those issue areas, see Slapin and Proksch (2008) <doi:10.1111/j.1540-5907.2008.00338.x>.

r-mirtcat 1.14
Propagated dependencies: r-shiny@1.11.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pbapply@1.7-4 r-mirt@1.45.1 r-markdown@2.0 r-lpsolve@5.6.23 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/philchalmers/mirtCAT
Licenses: GPL 3+
Build system: r
Synopsis: Computerized Adaptive Testing with Multidimensional Item Response Theory
Description:

This package provides tools to generate HTML interfaces for adaptive and non-adaptive tests using the shiny package (Chalmers (2016) <doi:10.18637/jss.v071.i05>). Suitable for applying unidimensional and multidimensional computerized adaptive tests (CAT) using item response theory methodology and for creating simple questionnaires forms to collect response data directly in R. Additionally, optimal test designs (e.g., "shadow testing") are supported for tests that contain a large number of item selection constraints. Finally, package contains tools useful for performing Monte Carlo simulations for studying test item banks.

r-mts 1.2.1
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-fgarch@4052.93 r-fbasics@4041.97
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MTS
Licenses: FSDG-compatible
Build system: r
Synopsis: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models
Description:

Multivariate Time Series (MTS) is a general package for analyzing multivariate linear time series and estimating multivariate volatility models. It also handles factor models, constrained factor models, asymptotic principal component analysis commonly used in finance and econometrics, and principal volatility component analysis. (a) For the multivariate linear time series analysis, the package performs model specification, estimation, model checking, and prediction for many widely used models, including vector AR models, vector MA models, vector ARMA models, seasonal vector ARMA models, VAR models with exogenous variables, multivariate regression models with time series errors, augmented VAR models, and Error-correction VAR models for co-integrated time series. For model specification, the package performs structural specification to overcome the difficulties of identifiability of VARMA models. The methods used for structural specification include Kronecker indices and Scalar Component Models. (b) For multivariate volatility modeling, the MTS package handles several commonly used models, including multivariate exponentially weighted moving-average volatility, Cholesky decomposition volatility models, dynamic conditional correlation (DCC) models, copula-based volatility models, and low-dimensional BEKK models. The package also considers multiple tests for conditional heteroscedasticity, including rank-based statistics. (c) Finally, the MTS package also performs forecasting using diffusion index , transfer function analysis, Bayesian estimation of VAR models, and multivariate time series analysis with missing values.Users can also use the package to simulate VARMA models, to compute impulse response functions of a fitted VARMA model, and to calculate theoretical cross-covariance matrices of a given VARMA model.

r-miesmuschel 0.0.4-3
Propagated dependencies: r-r6@2.6.1 r-paradox@1.0.1 r-mlr3misc@0.19.0 r-matrixstats@1.5.0 r-lgr@0.5.0 r-data-table@1.17.8 r-checkmate@2.3.3 r-bbotk@1.8.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/mlr-org/miesmuschel
Licenses: Expat
Build system: r
Synopsis: Mixed Integer Evolution Strategies
Description:

Evolutionary black box optimization algorithms building on the bbotk package. miesmuschel offers both ready-to-use optimization algorithms, as well as their fundamental building blocks that can be used to manually construct specialized optimization loops. The Mixed Integer Evolution Strategies as described by Li et al. (2013) <doi:10.1162/EVCO_a_00059> can be implemented, as well as the multi-objective optimization algorithms NSGA-II by Deb, Pratap, Agarwal, and Meyarivan (2002) <doi:10.1109/4235.996017>.

r-muvicp 1.3.2
Propagated dependencies: r-sm@2.2-6.0 r-mass@7.3-65 r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MuViCP
Licenses: GPL 3
Build system: r
Synopsis: MultiClass Visualizable Classification using Combination of Projections
Description:

An ensemble classifier for multiclass classification. This is a novel classifier that natively works as an ensemble. It projects data on a large number of matrices, and uses very simple classifiers on each of these projections. The results are then combined, ideally via Dempster-Shafer Calculus.

r-mapchina 0.1.0
Propagated dependencies: r-sf@1.0-23
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/xmc811/mapchina
Licenses: GPL 3
Build system: r
Synopsis: China Administrative Divisions Geospatial Shapefile Data
Description:

Geospatial shapefile data of China administrative divisions to the county/district-level.

r-mirtest 2.2
Propagated dependencies: r-mass@7.3-65 r-limma@3.66.0 r-globaltest@5.64.0 r-globalancova@4.28.0 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://pubmed.ncbi.nlm.nih.gov/22723856/
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Combined miRNA- And mRNA-Testing
Description:

Package for combined miRNA- and mRNA-testing.

r-mtarm 0.1.8
Propagated dependencies: r-progressr@0.18.0 r-mvtnorm@1.3-3 r-gigrvg@0.8 r-future-apply@1.20.0 r-future@1.68.0 r-formula@1.2-5 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/lhvanegasp/mtarm
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Bayesian Estimation of Multivariate Threshold Autoregressive Models
Description:

Estimation, inference and forecasting using the Bayesian approach for multivariate threshold autoregressive (TAR) models in which the distribution used to describe the noise process belongs to the class of Gaussian variance mixtures.

r-movementsync 0.1.5
Propagated dependencies: r-zoo@1.8-14 r-waveletcomp@1.2 r-tidyr@1.3.1 r-signal@1.8-1 r-scales@1.4.0 r-rlang@1.1.6 r-osfr@0.2.9 r-lmtest@0.9-40 r-igraph@2.2.1 r-hms@1.1.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-circular@0.5-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=movementsync
Licenses: Expat
Build system: r
Synopsis: Analysis and Visualisation of Musical Audio and Video Movement Synchrony Data
Description:

Analysis and visualisation of synchrony, interaction, and joint movements from audio and video movement data of a group of music performers. The demo is data described in Clayton, Leante, and Tarsitani (2021) <doi:10.17605/OSF.IO/KS325>, while example analyses can be found in Clayton, Jakubowski, and Eerola (2019) <doi:10.1177/1029864919844809>. Additionally, wavelet analysis techniques have been applied to examine movement-related musical interactions, as shown in Eerola et al. (2018) <doi:10.1098/rsos.171520>.

r-mte 1.2.1
Propagated dependencies: r-rqpen@4.2 r-quantreg@6.1 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/shaobo-li/MTE
Licenses: GPL 3
Build system: r
Synopsis: Maximum Tangent Likelihood Estimation for Robust Linear Regression and Variable Selection
Description:

Several robust estimators for linear regression and variable selection are provided. Included are Maximum tangent likelihood estimator by Qin, et al., (2017), arXiv preprint <doi:10.48550/arXiv.1708.05439>, least absolute deviance estimator and Huber regression. The penalized version of each of these estimator incorporates L1 penalty function, i.e., LASSO and Adaptive Lasso. They are able to produce consistent estimates for both fixed and high-dimensional settings.

r-metacycle 1.2.1
Propagated dependencies: r-gnm@1.1-5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MetaCycle
Licenses: GPL 2+
Build system: r
Synopsis: Evaluate Periodicity in Large Scale Data
Description:

There are two functions-meta2d and meta3d for detecting rhythmic signals from time-series datasets. For analyzing time-series datasets without individual information, meta2d is suggested, which could incorporates multiple methods from ARSER, JTK_CYCLE and Lomb-Scargle in the detection of interested rhythms. For analyzing time-series datasets with individual information, meta3d is suggested, which takes use of any one of these three methods to analyze time-series data individual by individual and gives out integrated values based on analysis result of each individual.

r-mixedmem 1.1.2
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-gtools@3.9.5 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mixedMem
Licenses: GPL 2+
Build system: r
Synopsis: Tools for Discrete Multivariate Mixed Membership Models
Description:

Fits mixed membership models with discrete multivariate data (with or without repeated measures) following the general framework of Erosheva et al (2004). This package uses a Variational EM approach by approximating the posterior distribution of latent memberships and selecting hyperparameters through a pseudo-MLE procedure. Currently supported data types are Bernoulli, multinomial and rank (Plackett-Luce). The extended GoM model with fixed stayers from Erosheva et al (2007) is now also supported. See Airoldi et al (2014) for other examples of mixed membership models.

r-miceconindex 0.1-8
Propagated dependencies: r-misctools@0.6-28
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://www.micEcon.org
Licenses: GPL 2+
Build system: r
Synopsis: Price and Quantity Indices
Description:

This package provides tools for calculating Laspeyres, Paasche, and Fisher price and quantity indices.

r-msaenet 3.1.2
Propagated dependencies: r-survival@3.8-3 r-ncvreg@3.16.0 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-glmnet@4.1-10 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://nanx.me/msaenet/
Licenses: GPL 3+
Build system: r
Synopsis: Multi-Step Adaptive Estimation Methods for Sparse Regressions
Description:

Multi-step adaptive elastic-net (MSAENet) algorithm for feature selection in high-dimensional regressions proposed in Xiao and Xu (2015) <DOI:10.1080/00949655.2015.1016944>, with support for multi-step adaptive MCP-net (MSAMNet) and multi-step adaptive SCAD-net (MSASNet) methods.

r-multirng 1.2.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiRNG
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Multivariate Pseudo-Random Number Generation
Description:

Pseudo-random number generation for 11 multivariate distributions: Normal, t, Uniform, Bernoulli, Hypergeometric, Beta (Dirichlet), Multinomial, Dirichlet-Multinomial, Laplace, Wishart, and Inverted Wishart. The details of the method are explained in Demirtas (2004) <DOI:10.22237/jmasm/1099268340>.

r-mvp 1.0-18
Propagated dependencies: r-rcpp@1.1.0 r-partitions@1.10-9 r-numbers@0.9-2 r-mpoly@1.1.2 r-magic@1.6-1 r-disordr@0.9-8-5 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/RobinHankin/mvp
Licenses: GPL 2+
Build system: r
Synopsis: Fast Symbolic Multivariate Polynomials
Description:

Fast manipulation of symbolic multivariate polynomials using the Map class of the Standard Template Library. The package uses print and coercion methods from the mpoly package but offers speed improvements. It is comparable in speed to the spray package for sparse arrays, but retains the symbolic benefits of mpoly'. To cite the package in publications, use Hankin 2022 <doi:10.48550/ARXIV.2210.15991>. Uses disordR discipline.

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