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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-mllrnrs 0.0.8
Propagated dependencies: r-r6@2.6.1 r-mlexperiments@1.0.0 r-kdry@0.0.3 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/kapsner/mllrnrs
Licenses: GPL 3+
Build system: r
Synopsis: R6-Based ML Learners for 'mlexperiments'
Description:

Enhances mlexperiments <https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners. The package provides R6-based learners for the following algorithms: glmnet <https://CRAN.R-project.org/package=glmnet>, ranger <https://CRAN.R-project.org/package=ranger>, xgboost <https://CRAN.R-project.org/package=xgboost>, and lightgbm <https://CRAN.R-project.org/package=lightgbm>. These can be used directly with the mlexperiments R package.

r-mcartest 1.3
Propagated dependencies: r-rdpack@2.6.4 r-rcsdp@0.1.57.6 r-rcpp@1.1.0 r-rcdd@1.6 r-pracma@2.4.6 r-norm@1.0-11.1 r-missmethods@0.4.0 r-matrix@1.7-4 r-mass@7.3-65 r-lpsolve@5.6.23 r-highs@1.12.0-1 r-gtools@3.9.5 r-epi@2.61 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=MCARtest
Licenses: Expat
Build system: r
Synopsis: Optimal Nonparametric Testing of Missing Completely at Random
Description:

This package provides functions for carrying out nonparametric hypothesis tests of the MCAR hypothesis based on the theory of Frechet classes and compatibility. Also gives functions for computing halfspace representations of the marginal polytope and related geometric objects.

r-mirrorselect 0.0.3
Propagated dependencies: r-yulab-utils@0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mirrorselect
Licenses: Artistic License 2.0
Build system: r
Synopsis: Test CRAN/Bioconductor Mirror Speed
Description:

Testing CRAN and Bioconductor mirror speed by recording download time of src/base/COPYING (for CRAN) and packages/release/bioc/html/ggtree.html (for Bioconductor).

r-mtsta 0.0.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/PaulESantos/mtsta
Licenses: Expat
Build system: r
Synopsis: Accessing the Red List of Montane Tree Species of the Tropical Andes
Description:

Access the Red List of Montane Tree Species of the Tropical Andes Tejedor Garavito et al.(2014, ISBN:978-1-905164-60-8). This package allows users to search for globally threatened tree species within the andean montane forests, including cloud forests and seasonal (wet) forests above 1500 m a.s.l.

r-mapsrinteractive 2.0.1
Propagated dependencies: r-terra@1.8-86 r-gstat@2.1-4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://CRAN.R-project.org/package=mapsRinteractive
Licenses: Expat
Build system: r
Synopsis: Local Adaptation and Evaluation of Raster Maps
Description:

Local adaptation and evaluation of maps of continuous attributes in raster format by use of point location data.

r-mic 2.0.0
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggh4x@0.3.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-amr@3.0.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/agerada/MIC
Licenses: GPL 3+
Build system: r
Synopsis: Analysis of Antimicrobial Minimum Inhibitory Concentration Data
Description:

Analyse, plot, and tabulate antimicrobial minimum inhibitory concentration (MIC) data. Validate the results of an MIC experiment by comparing observed MIC values to a gold standard assay, in line with standards from the International Organization for Standardization (2021) <https://www.iso.org/standard/79377.html>.

r-maoea 0.6.2
Dependencies: python-numpy@1.26.4
Propagated dependencies: r-stringr@1.6.0 r-reticulate@1.44.1 r-randtoolbox@2.0.5 r-pracma@2.4.6 r-nsga2r@1.1 r-nnet@7.3-20 r-mass@7.3-65 r-lhs@1.2.0 r-gtools@3.9.5 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/dots26/MaOEA
Licenses: GPL 3+
Build system: r
Synopsis: Many Objective Evolutionary Algorithm
Description:

This package provides a set of evolutionary algorithms to solve many-objective optimization. Hybridization between the algorithms are also facilitated. Available algorithms are: SMS-EMOA <doi:10.1016/j.ejor.2006.08.008> NSGA-III <doi:10.1109/TEVC.2013.2281535> MO-CMA-ES <doi:10.1145/1830483.1830573> The following many-objective benchmark problems are also provided: DTLZ1'-'DTLZ4 from Deb, et al. (2001) <doi:10.1007/1-84628-137-7_6> and WFG4'-'WFG9 from Huband, et al. (2005) <doi:10.1109/TEVC.2005.861417>.

r-mediationsens 0.0.3
Propagated dependencies: r-mediation@4.5.1 r-distr@2.9.7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mediationsens
Licenses: GPL 2
Build system: r
Synopsis: Simulation-Based Sensitivity Analysis for Causal Mediation Studies
Description:

Simulation-based sensitivity analysis for causal mediation studies. It numerically and graphically evaluates the sensitivity of causal mediation analysis results to the presence of unmeasured pretreatment confounding. The proposed method has primary advantages over existing methods. First, using an unmeasured pretreatment confounder conditional associations with the treatment, mediator, and outcome as sensitivity parameters, the method enables users to intuitively assess sensitivity in reference to prior knowledge about the strength of a potential unmeasured pretreatment confounder. Second, the method accurately reflects the influence of unmeasured pretreatment confounding on the efficiency of estimation of the causal effects. Third, the method can be implemented in different causal mediation analysis approaches, including regression-based, simulation-based, and propensity score-based methods. It is applicable to both randomized experiments and observational studies.

r-molhd 0.2
Propagated dependencies: r-fields@17.1 r-arrangements@1.1.9
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MOLHD
Licenses: LGPL 2.0+
Build system: r
Synopsis: Multiple Objective Latin Hypercube Design
Description:

Generate the optimal maximin distance, minimax distance (only for low dimensions), and maximum projection designs within the class of Latin hypercube designs efficiently for computer experiments. Generate Pareto front optimal designs for each two of the three criteria and all the three criteria within the class of Latin hypercube designs efficiently. Provide criterion computing functions. References of this package can be found in Morris, M. D. and Mitchell, T. J. (1995) <doi:10.1016/0378-3758(94)00035-T>, Lu Lu and Christine M. Anderson-CookTimothy J. Robinson (2011) <doi:10.1198/Tech.2011.10087>, Joseph, V. R., Gul, E., and Ba, S. (2015) <doi:10.1093/biomet/asv002>.

r-mtps 1.0.2
Propagated dependencies: r-rpart@4.1.24 r-mass@7.3-65 r-glmnet@4.1-10 r-e1071@1.7-16 r-class@7.3-23
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://doi.org/10.1093/bioinformatics/btz531
Licenses: GPL 2+
Build system: r
Synopsis: Multi-Task Prediction using Stacking Algorithms
Description:

Simultaneous multiple outcomes prediction based on revised stacking algorithms, which enables the integration of information from predictions of individual models. An implementation of methodologies proposed in our paper: Li Xing, Mary L Lesperance, Xuekui Zhang. (2019) Bioinformatics, "Simultaneous prediction of multiple outcomes using revised stacking algorithms" <doi:10.1093/bioinformatics/btz531>.

r-mapstats 3.2
Propagated dependencies: r-ttutils@1.0-1.1 r-survey@4.4-8 r-sp@2.2-0 r-sf@1.0-23 r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-lattice@0.22-7 r-hmisc@5.2-4 r-colorspace@2.1-2 r-classint@0.4-11
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mapStats
Licenses: GPL 2+
Build system: r
Synopsis: Geographic Display of Survey Data Statistics
Description:

Automated calculation and visualization of survey data statistics on a color-coded (choropleth) map.

r-mixturemissing 3.0.6
Propagated dependencies: r-numderiv@2016.8-1.1 r-mvtnorm@1.3-3 r-mnormt@2.1.1 r-mice@3.18.0 r-mclust@6.1.2 r-mass@7.3-65 r-cluster@2.1.8.1 r-bessel@0.7-0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MixtureMissing
Licenses: GPL 2+
Build system: r
Synopsis: Robust and Flexible Model-Based Clustering for Data Sets with Missing Values at Random
Description:

Implementations of various robust and flexible model-based clustering methods for data sets with missing values at random (Tong and Tortora, 2025, <doi:10.18637/jss.v115.i03>). Two main models are: Multivariate Contaminated Normal Mixture (MCNM, Tong and Tortora, 2022, <doi:10.1007/s11634-021-00476-1>) and Multivariate Generalized Hyperbolic Mixture (MGHM, Wei et al., 2019, <doi:10.1016/j.csda.2018.08.016>). Mixtures via some special or limiting cases of the multivariate generalized hyperbolic distribution are also included: Normal-Inverse Gaussian, Symmetric Normal-Inverse Gaussian, Skew-Cauchy, Cauchy, Skew-t, Student's t, Normal, Symmetric Generalized Hyperbolic, Hyperbolic Univariate Marginals, Hyperbolic, and Symmetric Hyperbolic. Funding: This work was partially supported by the National Science foundation NSF Grant NO. 2209974.

r-matrixlaplacian 1.0
Propagated dependencies: r-scatterplot3d@0.3-44
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=matrixLaplacian
Licenses: GPL 2
Build system: r
Synopsis: Normalized Laplacian Matrix and Laplacian Map
Description:

Constructs the normalized Laplacian matrix of a square matrix, returns the eigenvectors (singular vectors) and visualization of normalized Laplacian map.

r-madr 1.0.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=madr
Licenses: GPL 3
Build system: r
Synopsis: Model Averaged Double Robust Estimation
Description:

Estimates average treatment effects using model average double robust (MA-DR) estimation. The MA-DR estimator is defined as weighted average of double robust estimators, where each double robust estimator corresponds to a specific choice of the outcome model and the propensity score model. The MA-DR estimator extend the desirable double robustness property by achieving consistency under the much weaker assumption that either the true propensity score model or the true outcome model be within a specified, possibly large, class of models.

r-metadynminer3d 0.0.2
Propagated dependencies: r-rgl@1.3.31 r-rcpp@1.1.0 r-misc3d@0.9-1 r-metadynminer@0.1.7
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://metadynamics.cz/metadynminer3d/
Licenses: GPL 3
Build system: r
Synopsis: Tools to Read, Analyze and Visualize Metadynamics 3D HILLS Files from 'Plumed'
Description:

Metadynamics is a state of the art biomolecular simulation technique. Plumed Tribello, G.A. et al. (2014) <doi:10.1016/j.cpc.2013.09.018> program makes it possible to perform metadynamics using various simulation codes. The results of metadynamics done in Plumed can be analyzed by metadynminer'. The package metadynminer reads 1D and 2D metadynamics hills files from Plumed package. As an addendum, metadynaminer3d is used to visualize 3D hills. It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) <doi:10.1016/j.cpc.2015.08.037> to calculate a free energy surface from hills. Minima can be located and plotted on the free energy surface. Free energy surfaces and minima can be plotted to produce publication quality images.

r-masscor 0.0.7.1
Propagated dependencies: r-metrology@0.9-29-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=masscor
Licenses: GPL 3+
Build system: r
Synopsis: Mass Measurement Corrections
Description:

Mass measurement corrections and uncertainties using calibration data, as recommended by EURAMET's guideline No. 18 (2015) ISBN:978-3-942992-40-4 . The package provides classes, functions, and methods for storing information contained in calibration certificates and converting balance readings to both conventional mass and real mass. For the latter, the Magnitude of the Air Buoyancy Correction factor employs models (such as the CIMP-2007 formula revised by Picard, Davis, Gläser, and Fujii (2008) <doi:10.1088/0026-1394/45/2/004>) to estimate the local air density using measured environmental conditions.

r-mcptools 0.2.0
Propagated dependencies: r-rlang@1.1.6 r-promises@1.5.0 r-processx@3.8.6 r-nanonext@1.7.2 r-jsonlite@2.0.0 r-httr2@1.2.1 r-httpuv@1.6.16 r-ellmer@0.4.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/posit-dev/mcptools
Licenses: Expat
Build system: r
Synopsis: Model Context Protocol Servers and Clients
Description:

This package implements the Model Context Protocol (MCP). Users can start R'-based servers, serving functions as tools for large language models to call before responding to the user in MCP-compatible apps like Claude Desktop and Claude Code', with options to run those tools inside of interactive R sessions. On the other end, when R is the client via the ellmer package, users can register tools from third-party MCP servers to integrate additional context into chats.

r-medicaldata 0.2.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://higgi13425.github.io/medicaldata/
Licenses: Expat
Build system: r
Synopsis: Data Package for Medical Datasets
Description:

This package provides access to well-documented medical datasets for teaching. Featuring several from the Teaching of Statistics in the Health Sciences website <https://www.causeweb.org/tshs/category/dataset/>, a few reconstructed datasets of historical significance in medical research, some reformatted and extended from existing R packages, and some data donations.

r-mkssd 1.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=mkssd
Licenses: GPL 2+
Build system: r
Synopsis: Efficient Multi-Level k-Circulant Supersaturated Designs
Description:

Generates efficient balanced non-aliased multi-level k-circulant supersaturated designs by interchanging the elements of the generator vector. Attempts to generate a supersaturated design that has chisquare efficiency more than user specified efficiency level (mef). Displays the progress of generation of an efficient multi-level k-circulant design through a progress bar. The progress of 100% means that one full round of interchange is completed. More than one full round (typically 4-5 rounds) of interchange may be required for larger designs.

r-metacom 1.5.3
Propagated dependencies: r-vegan@2.7-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=metacom
Licenses: GPL 2
Build system: r
Synopsis: Analysis of the 'Elements of Metacommunity Structure'
Description:

This package provides functions to analyze coherence, boundary clumping, and turnover following the pattern-based metacommunity analysis of Leibold and Mikkelson 2002 <doi:10.1034/j.1600-0706.2002.970210.x>. The package also includes functions to visualize ecological networks, and to calculate modularity as a replacement to boundary clumping.

r-multirec 1.0.6
Propagated dependencies: r-survival@3.8-3 r-rfast@2.1.5.2 r-numderiv@2016.8-1.1 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=multiRec
Licenses: GPL 2
Build system: r
Synopsis: Analysis of Multi-Type Recurrent Events
Description:

This package implements likelihood-based estimation and diagnostics for multi-type recurrent event data with dynamic risk that depends on prior events and accommodates terminating events. Methods are described in Ghosh, Chan, Younes and Davis (2023) "A Dynamic Risk Model for Multitype Recurrent Events" <doi:10.1093/aje/kwac213>.

r-minimap 0.1.0
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://github.com/seankross/minimap
Licenses: Expat
Build system: r
Synopsis: Create Tile Grid Maps
Description:

Create tile grid maps, which are like choropleth maps except each region is represented with equal visual space.

r-mlr3benchmark 0.1.7
Propagated dependencies: r-r6@2.6.1 r-mlr3misc@0.19.0 r-ggplot2@4.0.1 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://mlr3benchmark.mlr-org.com
Licenses: LGPL 3
Build system: r
Synopsis: Analysis and Visualisation of Benchmark Experiments
Description:

This package implements methods for post-hoc analysis and visualisation of benchmark experiments, for mlr3 and beyond.

r-minter 0.1.0
Propagated dependencies: r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://fdecunta.github.io/minter/
Licenses: Expat
Build system: r
Synopsis: Effect Sizes for Meta-Analysis of Interactions from Factorial Experiments
Description:

Compute effect sizes and their sampling variances from factorial experimental designs. The package supports calculation of simple effects, overall effects, and interaction effects for use in factorial meta-analyses. See Gurevitch et al. (2000) <doi:10.1086/303337>, Morris et al. (2007) <doi:10.1890/06-0442>, Lajeunesse (2011) <doi:10.1890/11-0423.1> and Macartney et al. (2022) <doi:10.1016/j.neubiorev.2022.104554>.

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