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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-mswm 1.5
Propagated dependencies: r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MSwM
Licenses: GPL 2+
Build system: r
Synopsis: Fitting Markov Switching Models
Description:

Estimation, inference and diagnostics for Univariate Autoregressive Markov Switching Models for Linear and Generalized Models. Distributions for the series include gaussian, Poisson, binomial and gamma cases. The EM algorithm is used for estimation (see Perlin (2012) <doi:10.2139/ssrn.1714016>).

r-monomvn 1.9-21
Propagated dependencies: r-quadprog@1.5-8 r-pls@2.8-5 r-mvtnorm@1.3-3 r-mass@7.3-65 r-lars@1.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://bobby.gramacy.com/r_packages/monomvn/
Licenses: LGPL 2.0+
Build system: r
Synopsis: Estimation for MVN and Student-t Data with Monotone Missingness
Description:

Estimation of multivariate normal (MVN) and student-t data of arbitrary dimension where the pattern of missing data is monotone. See Pantaleo and Gramacy (2010) <doi:10.48550/arXiv.0907.2135>. Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, the package can handle a nearly arbitrary amount of missing data. The current version supports maximum likelihood inference and a full Bayesian approach employing scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided.

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-mixak 5.8
Propagated dependencies: r-mnormt@2.1.1 r-lme4@1.1-37 r-fastghquad@1.0.1 r-colorspace@2.1-2 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://msekce.karlin.mff.cuni.cz/~komarek/
Licenses: GPL 3+
Build system: r
Synopsis: Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering
Description:

This package contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models. The package is primarily related to the publications Komárek (2009, Comp. Stat. and Data Anal.) <doi:10.1016/j.csda.2009.05.006> and Komárek and Komárková (2014, J. of Stat. Soft.) <doi:10.18637/jss.v059.i12>. It also implements methods published in Komárek and Komárková (2013, Ann. of Appl. Stat.) <doi:10.1214/12-AOAS580>, Hughes, Komárek, Bonnett, Czanner, Garcà a-Fiñana (2017, Stat. in Med.) <doi:10.1002/sim.7397>, Jaspers, Komárek, Aerts (2018, Biom. J.) <doi:10.1002/bimj.201600253> and Hughes, Komárek, Czanner, Garcà a-Fiñana (2018, Stat. Meth. in Med. Res) <doi:10.1177/0962280216674496>.

r-mrbin 1.9.5
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/kleinomicslab/mrbin
Licenses: GPL 3
Build system: r
Synopsis: Metabolomics Data Analysis Functions
Description:

This package provides a collection of functions for processing and analyzing metabolite data. The namesake function mrbin() converts 1D or 2D Nuclear Magnetic Resonance data into a matrix of values suitable for further data analysis and performs basic processing steps in a reproducible way. Negative values, a common issue in such data, can be replaced by positive values (<doi:10.1021/acs.jproteome.0c00684>). All used parameters are stored in a readable text file and can be restored from that file to enable exact reproduction of the data at a later time. The function fia() ranks features according to their impact on classifier models, especially artificial neural network models.

r-msg 0.9
Propagated dependencies: r-rcolorbrewer@1.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/yihui/MSG
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Data and Functions for the Book Modern Statistical Graphics
Description:

This package provides a companion to the Chinese book ``Modern Statistical Graphics''.

r-midr 0.5.3
Propagated dependencies: r-rlang@1.1.6 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://github.com/ryo-asashi/midr
Licenses: Expat
Build system: r
Synopsis: Learning from Black-Box Models by Maximum Interpretation Decomposition
Description:

The goal of midr is to provide a model-agnostic method for interpreting and explaining black-box predictive models by creating a globally interpretable surrogate model. The package implements Maximum Interpretation Decomposition (MID), a functional decomposition technique that finds an optimal additive approximation of the original model. This approximation is achieved by minimizing the squared error between the predictions of the black-box model and the surrogate model. The theoretical foundations of MID are described in Iwasawa & Matsumori (2025) [Forthcoming], and the package itself is detailed in Asashiba et al. (2025) <doi:10.48550/arXiv.2506.08338>.

r-mgwrhw 1.1.1.5
Propagated dependencies: r-tidyr@1.3.1 r-spgwr@0.6-37 r-sf@1.0-23 r-psych@2.5.6 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://cran.r-project.org/package=mgwrhw
Licenses: GPL 3
Build system: r
Synopsis: Displays GWR (Geographically Weighted Regression) and Mixed GWR Output and Map
Description:

Display processing results using the GWR (Geographically Weighted Regression) method, display maps, and show the results of the Mixed GWR (Mixed Geographically Weighted Regression) model which automatically selects global variables based on variability between regions. This function refers to Yasin, & Purhadi. (2012). "Mixed Geographically Weighted Regression Model (Case Study the Percentage of Poor Households in Mojokerto 2008)". European Journal of Scientific Research, 188-196. <https://www.researchgate.net/profile/Hasbi-Yasin-2/publication/289689583_Mixed_geographically_weighted_regression_model_case_study_The_percentage_of_poor_households_in_Mojokerto_2008/links/58e46aa40f7e9bbe9c94d641/Mixed-geographically-weighted-regression-model-case-study-The-percentage-of-poor-households-in-Mojokerto-2008.pdf>.

r-missingplotlsd 0.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MissingPlotLSD
Licenses: GPL 3
Build system: r
Synopsis: Missing Plot in LSD
Description:

This package provides a system for Analysis of LSD when there is one missing observation. Methods for this process is described in A.M.Gun,M.K.Gupta,B.Dasgupta(2019,ISBN:81-87567-81-3).

r-monoclust 1.2.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-permute@0.9-8 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://vinhtantran.github.io/monoClust/
Licenses: GPL 2+
Build system: r
Synopsis: Perform Monothetic Clustering with Extensions to Circular Data
Description:

Implementation of the Monothetic Clustering algorithm (Chavent, 1998 <doi:10.1016/S0167-8655(98)00087-7>) on continuous data sets. A lot of extensions are included in the package, including applying Monothetic clustering on data sets with circular variables, visualizations with the results, and permutation and cross-validation based tests to support the decision on the number of clusters.

r-microbialgrowth 1.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MicrobialGrowth
Licenses: GPL 3+
Build system: r
Synopsis: Estimates Growth Parameters from Models and Plots the Curve
Description:

Fit growth curves to various known microbial growth models automatically to estimate growth parameters. Growth curves can be plotted with their uncertainty band. Growth models are: modified Gompertz model (Zwietering et al. (1990) <doi:10.1128/aem.56.6.1875-1881.1990>), Baranyi model (Baranyi and Roberts (1994) <doi:10.1016/0168-1605%2894%2990157-0>), Rosso model (Rosso et al. (1993) <doi:10.1006/jtbi.1993.1099>) and linear model (Dantigny (2005) <doi:10.1016/j.ijfoodmicro.2004.10.013>).

r-mixtur 1.2.2
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 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/JimGrange/mixtur
Licenses: GPL 3
Build system: r
Synopsis: Modelling Continuous Report Visual Short-Term Memory Studies
Description:

This package provides a set of utility functions for analysing and modelling data from continuous report short-term memory experiments using either the 2-component mixture model of Zhang and Luck (2008) <doi:10.1038/nature06860> or the 3-component mixture model of Bays et al. (2009) <doi:10.1167/9.10.7>. Users are also able to simulate from these models.

r-mixfmri 0.1-4
Propagated dependencies: r-rcolorbrewer@1.1-3 r-mixsim@1.1-8 r-matrix@1.7-4 r-mass@7.3-65 r-fftw@1.0-9 r-emcluster@0.2-17
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/snoweye/MixfMRI
Licenses: FSDG-compatible
Build system: r
Synopsis: Mixture fMRI Clustering Analysis
Description:

Utilizing model-based clustering (unsupervised) for functional magnetic resonance imaging (fMRI) data. The developed methods (Chen and Maitra (2023) <doi:10.1002/hbm.26425>) include 2D and 3D clustering analyses (for p-values with voxel locations) and segmentation analyses (for p-values alone) for fMRI data where p-values indicate significant level of activation responding to stimulate of interesting. The analyses are mainly identifying active voxel/signal associated with normal brain behaviors. Analysis pipelines (R scripts) utilizing this package (see examples in inst/workflow/') is also implemented with high performance techniques.

r-maldirppa 1.1.0-3
Propagated dependencies: r-waveslim@1.8.5 r-signal@1.8-1 r-robustbase@0.99-6 r-maldiquant@1.22.3 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/Japal/MALDIrppa
Licenses: GPL 2+
Build system: r
Synopsis: MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis
Description:

This package provides methods for quality control and robust pre-processing and analysis of MALDI mass spectrometry data (Palarea-Albaladejo et al. (2018) <doi:10.1093/bioinformatics/btx628>).

r-maplamina 0.1.0
Propagated dependencies: r-sf@1.0-23 r-htmlwidgets@1.6.4 r-digest@0.6.39 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/jhumbl/maplamina
Licenses: Expat
Build system: r
Synopsis: High-Performance 'WebGL' Mapping Widgets for R
Description:

This package creates interactive maps using MapLibre GL and deck.gl via htmlwidgets'. Provides GPU-accelerated layers for points, lines and polygons, plus linked user interface components such as filters, views and summary cards for exploratory analysis and production dashboards.

r-markstat 0.1.5
Propagated dependencies: r-tidyr@1.3.1 r-spatstat-utils@3.2-0 r-spatstat-univar@3.1-5 r-spatstat-random@3.4-3 r-spatstat-linnet@3.3-2 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-patchwork@1.3.2 r-ggplot2@4.0.1 r-get@1.0-7 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=markstat
Licenses: GPL 2+
Build system: r
Synopsis: Mark Correlation Functions for Spatial Point Patterns
Description:

This package provides a range of functions for computing both global and local mark correlation functions for spatial point patterns in either Euclidean spaces or on linear networks, with points carrying either real-valued or function-valued marks. For a review of mark correlation functions, see Eckardt and Moradi (2024) <doi:10.1007/s13253-024-00605-1>.

r-mannwhitneycopula 0.1.1
Propagated dependencies: r-tidyverse@2.0.0 r-tidyr@1.3.1 r-survival@3.8-3 r-purrr@1.2.0 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://cran.r-project.org/package=MannWhitneyCopula
Licenses: Expat
Build system: r
Synopsis: Computing Mann-Whitney Effect Based on Copulas
Description:

Computing the Mann-Whitney effect based on copula models. Estimation of the association parameter in survival copula models. A description of the underlying methods is described in Nakazono et al. (2024) <doi:10.3390/math12101453> and Nakazono et al. (accepted for publication in Statistical Papers).

r-mlr3oml 0.12.0
Propagated dependencies: r-withr@3.0.2 r-uuid@1.2-1 r-stringi@1.8.7 r-r6@2.6.1 r-paradox@1.0.1 r-mlr3misc@0.19.0 r-mlr3@1.2.0 r-lgr@0.5.0 r-jsonlite@2.0.0 r-data-table@1.17.8 r-curl@7.0.0 r-checkmate@2.3.3 r-bit64@4.6.0-1 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mlr3oml.mlr-org.com
Licenses: LGPL 3
Build system: r
Synopsis: Connector Between 'mlr3' and 'OpenML'
Description:

This package provides an interface to OpenML.org to list and download machine learning data, tasks and experiments. The OpenML objects can be automatically converted to mlr3 objects. For a more sophisticated interface with more upload options, see the OpenML package.

r-michelrodange 1.0.0
Propagated dependencies: r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/b-rodrigues/michelRodange
Licenses: CC0
Build system: r
Synopsis: The Works (in Luxembourguish) of Michel Rodange
Description:

Michel Rodange was a Luxembourguish writer and poet who lived in the 19th century. His most notable work is Rodange (1872, ISBN:1166177424), ("Renert oder de Fuuà am Frack an a Ma'nsgrëà t"), but he also wrote many more works, including Rodange, Tockert (1928) <https://www.autorenlexikon.lu/page/document/361/3614/1/FRE/index.html> ("D'Léierchen - Dem Léiweckerche säi Lidd") and Rodange, Welter (1929) <https://www.autorenlexikon.lu/page/document/361/3615/1/FRE/index.html> ("Dem Grow Sigfrid seng Goldkuommer"). This package contains three datasets, each made from the plain text versions of his works available on <https://data.public.lu/fr/datasets/the-works-in-luxembourguish-of-michel-rodange/>.

r-mlergm 0.8.1
Propagated dependencies: r-stringr@1.6.0 r-statnet-common@4.12.0 r-sna@2.8 r-reshape2@1.4.5 r-plyr@1.8.9 r-network@1.19.0 r-matrix@1.7-4 r-lpsolve@5.6.23 r-ggplot2@4.0.1 r-ggally@2.4.0 r-ergm@4.12.0 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=mlergm
Licenses: GPL 3
Build system: r
Synopsis: Multilevel Exponential-Family Random Graph Models
Description:

Estimates exponential-family random graph models for multilevel network data, assuming the multilevel structure is observed. The scope, at present, covers multilevel models where the set of nodes is nested within known blocks. The estimation method uses Monte-Carlo maximum likelihood estimation (MCMLE) methods to estimate a variety of canonical or curved exponential family models for binary random graphs. MCMLE methods for curved exponential-family random graph models can be found in Hunter and Handcock (JCGS, 2006). The package supports parallel computing, and provides methods for assessing goodness-of-fit of models and visualization of networks.

r-majminkmeans 0.1.0
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MajMinKmeans
Licenses: GPL 3
Build system: r
Synopsis: k-Means Algorithm with a Majorization-Minimization Method
Description:

This package provides a hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) <doi:10.1137/140957639>. The two most important functions in package MajMinKmeans are cluster_km() and cluster_MajKm(). Cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering. Another useful function is MajMinOptim(), which helps to find the optimum values of the Majorization-Minimization estimator.

r-mombf 3.5.4
Propagated dependencies: r-survival@3.8-3 r-sparsematrixstats@1.22.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-ncvreg@3.16.0 r-mvtnorm@1.3-3 r-mgcv@1.9-4 r-mclust@6.1.2 r-matrix@1.7-4 r-intervals@0.15.5 r-glmnet@4.1-10 r-glasso@1.11 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/davidrusi/mombf
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Model Selection with Bayesian Methods and Information Criteria
Description:

Model selection and averaging for regression and mixtures, inclusing Bayesian model selection and information criteria (BIC, EBIC, AIC, GIC).

r-mixchar 0.1.0
Propagated dependencies: r-zoo@1.8-14 r-tmvtnorm@1.7 r-nloptr@2.2.1 r-minpack-lm@1.2-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://github.com/smwindecker/mixchar
Licenses: Expat
Build system: r
Synopsis: Mixture Model for the Deconvolution of Thermal Decay Curves
Description:

Deconvolution of thermal decay curves allows you to quantify proportions of biomass components in plant litter. Thermal decay curves derived from thermogravimetric analysis (TGA) are imported, modified, and then modelled in a three- or four- part mixture model using the Fraser-Suzuki function. The output is estimates for weights of pseudo-components corresponding to hemicellulose, cellulose, and lignin. For more information see: Müller-Hagedorn, M. and Bockhorn, H. (2007) <doi:10.1016/j.jaap.2006.12.008>, à rfão, J. J. M. and Figueiredo, J. L. (2001) <doi:10.1016/S0040-6031(01)00634-7>, and Yang, H. and Yan, R. and Chen, H. and Zheng, C. and Lee, D. H. and Liang, D. T. (2006) <doi:10.1021/ef0580117>.

r-mvet 0.1.0
Propagated dependencies: r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/YeonSeok-Choi/MVET
Licenses: Expat
Build system: r
Synopsis: Multivariate Estimates and Tests
Description:

Multivariate estimation and testing, currently a package for testing parametric data. To deal with parametric data, various multivariate normality tests and outlier detection are performed and visualized using the ggplot2 package. Homogeneity tests for covariance matrices are also possible, as well as the Hotelling's T-square test and the multivariate analysis of variance test. We are exploring additional tests and visualization techniques, such as profile analysis and randomized complete block design, to be made available in the future and making them easily accessible to users.

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