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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-clusterwebapp 0.1.3
Propagated dependencies: r-tidyr@1.3.1 r-shinythemes@1.2.0 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-rtsne@0.17 r-mlbench@2.1-6 r-mclust@6.1.2 r-magrittr@2.0.4 r-kernlab@0.9-33 r-ggplot2@4.0.1 r-factoextra@1.0.7 r-dt@0.34.0 r-dplyr@1.1.4 r-dbscan@1.2.3 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clusterWebApp
Licenses: Expat
Build system: r
Synopsis: Universal Clustering Analysis Platform
Description:

An interactive platform for clustering analysis and teaching based on the shiny web application framework. Supports multiple popular clustering algorithms including k-means, hierarchical clustering, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), PAM (Partitioning Around Medoids), GMM (Gaussian Mixture Model), and spectral clustering. Users can upload datasets or use built-in ones, visualize clustering results using dimensionality reduction methods such as Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE), evaluate clustering quality via silhouette plots, and explore method-specific visualizations and guides. For details on implemented methods, see: Reynolds (2009, ISBN:9781598296975) for GMM; Luxburg (2007) <doi:10.1007/s11222-007-9033-z> for spectral clustering.

r-climprojdiags 0.3.5
Propagated dependencies: r-multiapply@2.1.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://gitlab.earth.bsc.es/es/ClimProjDiags
Licenses: GPL 3
Build system: r
Synopsis: Set of Tools to Compute Various Climate Indices
Description:

Set of tools to compute metrics and indices for climate analysis. The package provides functions to compute extreme indices, evaluate the agreement between models and combine theses models into an ensemble. Multi-model time series of climate indices can be computed either after averaging the 2-D fields from different models provided they share a common grid or by combining time series computed on the model native grid. Indices can be assigned weights and/or combined to construct new indices. The package makes use of some of the methods described in: N. Manubens et al. (2018) <doi:10.1016/j.envsoft.2018.01.018>.

r-ctmle 0.1.2
Propagated dependencies: r-tmle@2.1.1 r-superlearner@2.0-29 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ctmle
Licenses: GPL 2
Build system: r
Synopsis: Collaborative Targeted Maximum Likelihood Estimation
Description:

This package implements the general template for collaborative targeted maximum likelihood estimation. It also provides several commonly used C-TMLE instantiation, like the vanilla/scalable variable-selection C-TMLE (Ju et al. (2017) <doi:10.1177/0962280217729845>) and the glmnet-C-TMLE algorithm (Ju et al. (2017) <arXiv:1706.10029>).

r-cepp 1.7
Propagated dependencies: r-trust@0.1-8 r-randtoolbox@2.0.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cepp
Licenses: GPL 3
Build system: r
Synopsis: Context Driven Exploratory Projection Pursuit
Description:

This package provides functions and Data to support Context Driven Exploratory Projection Pursuit.

r-condgee 0.2.0
Propagated dependencies: r-rootsolve@1.8.2.4 r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=condGEE
Licenses: GPL 2+
Build system: r
Synopsis: Parameter Estimation in Conditional GEE for Recurrent Event Gap Times
Description:

Solves for the mean parameters, the variance parameter, and their asymptotic variance in a conditional GEE for recurrent event gap times, as described by Clement and Strawderman (2009) in the journal Biostatistics. Makes a parametric assumption for the length of the censored gap time.

r-ctbi 2.0.5
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/fritte2/ctbi
Licenses: GPL 3
Build system: r
Synopsis: Procedure to Clean, Decompose and Aggregate Timeseries
Description:

Clean, decompose and aggregate univariate time series following the procedure "Cyclic/trend decomposition using bin interpolation" and the Logbox method for flagging outliers, both detailed in Ritter, F.: Technical note: A procedure to clean, decompose, and aggregate time series, Hydrol. Earth Syst. Sci., 27, 349â 361, <doi:10.5194/hess-27-349-2023>, 2023.

r-combat 0.0.4
Propagated dependencies: r-mvtnorm@1.3-3 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=COMBAT
Licenses: GPL 2
Build system: r
Synopsis: Combined Association Test for Genes using Summary Statistics
Description:

Genome-wide association studies (GWAS) have been widely used for identifying common variants associated with complex diseases. Due to the small effect sizes of common variants, the power to detect individual risk variants is generally low. Complementary to SNP-level analysis, a variety of gene-based association tests have been proposed. However, the power of existing gene-based tests is often dependent on the underlying genetic models, and it is not known a priori which test is optimal. Here we proposed COMBined Association Test (COMBAT) to incorporate strengths from multiple existing gene-based tests, including VEGAS, GATES and simpleM. Compared to individual tests, COMBAT shows higher overall performance and robustness across a wide range of genetic models. The algorithm behind this method is described in Wang et al (2017) <doi:10.1534/genetics.117.300257>.

r-cast 1.0.4
Propagated dependencies: r-zoo@1.8-14 r-twosamples@2.0.1 r-terra@1.8-86 r-sp@2.2-0 r-sf@1.0-23 r-plyr@1.8.9 r-ggplot2@4.0.1 r-forcats@1.0.1 r-fnn@1.1.4.1 r-data-table@1.17.8 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/HannaMeyer/CAST
Licenses: GPL 2+
Build system: r
Synopsis: 'caret' Applications for Spatial-Temporal Models
Description:

Supporting functionality to run caret with spatial or spatial-temporal data. caret is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using caret'. It includes the newly suggested Nearest neighbor distance matching cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; Linnenbrink et al. (2024) <doi:10.5194/gmd-17-5897-2024>; Schumacher et al. (2025) <doi:10.5194/gmd-18-10185-2025>. The package is described in detail in Meyer et al. (2026) <doi:10.1007/978-3-031-99665-8_11>.

r-coxplus 1.5.7
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CoxPlus
Licenses: GPL 3+
Build system: r
Synopsis: Cox Regression (Proportional Hazards Model) with Multiple Causes and Mixed Effects
Description:

Extends the Cox model to events with more than one causes. Also supports random and fixed effects, tied events, and time-varying variables. Model details are provided in Peng et al. (2018) <doi:10.1509/jmr.14.0643>.

r-contentanalysis 0.2.1
Propagated dependencies: r-visnetwork@2.1.4 r-tidytext@0.4.3 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-purrr@1.2.0 r-pdftools@3.6.0 r-openalexr@3.0.1 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-igraph@2.2.1 r-httr2@1.2.1 r-dplyr@1.1.4 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/massimoaria/contentanalysis
Licenses: GPL 3+
Build system: r
Synopsis: Scientific Content and Citation Analysis from PDF Documents
Description:

This package provides comprehensive tools for extracting and analyzing scientific content from PDF documents, including citation extraction, reference matching, text analysis, and bibliometric indicators. Supports multi-column PDF layouts, CrossRef API <https://www.crossref.org/documentation/retrieve-metadata/rest-api/> integration, and advanced citation parsing.

r-comorbidpgs 1.0.0
Propagated dependencies: r-nnet@7.3-20 r-mass@7.3-65 r-ivreg@0.6-5 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=comorbidPGS
Licenses: GPL 3+
Build system: r
Synopsis: Assessing Predisposition Between Phenotypes using Polygenic Scores
Description:

Using polygenic scores (PGS, or PRS/GRS for binary outcomes), this package allows to investigate shared predisposition between different conditions, and do fast association analysis, export plots and views of the PGS distribution using ggplot2 object.

r-colorhcplot 1.5.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=colorhcplot
Licenses: GPL 3
Build system: r
Synopsis: Colorful Hierarchical Clustering Dendrograms
Description:

Build dendrograms with sample groups highlighted by different colors. Visualize results of hierarchical clustering analyses as dendrograms whose leaves and labels are colored according to sample grouping. Assess whether data point grouping aligns to naturally occurring clusters.

r-cgmguru 0.1.0
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/shstat1729/cgmguru
Licenses: Expat
Build system: r
Synopsis: Advanced Continuous Glucose Monitoring Analysis with High-Performance C++ Backend
Description:

This package provides tools for advanced analysis of continuous glucose monitoring (CGM) time-series, implementing GRID (Glucose Rate Increase Detector) and GRID-based algorithms for postprandial peak detection, and detection of hypoglycemic and hyperglycemic episodes (Levels 1/2/Extended) aligned with international consensus CGM metrics. Core algorithms are implemented in optimized C++ using Rcpp to provide accurate and fast analysis on large datasets.

r-chromote 0.5.1
Propagated dependencies: r-zip@2.3.3 r-withr@3.0.2 r-websocket@1.4.4 r-rlang@1.1.6 r-r6@2.6.1 r-promises@1.5.0 r-processx@3.8.6 r-magrittr@2.0.4 r-later@1.4.4 r-jsonlite@2.0.0 r-fastmap@1.2.0 r-curl@7.0.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://rstudio.github.io/chromote/
Licenses: Expat
Build system: r
Synopsis: Headless Chrome Web Browser Interface
Description:

An implementation of the Chrome DevTools Protocol', for controlling a headless Chrome web browser.

r-coenoflex 2.2-0
Propagated dependencies: r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=coenoflex
Licenses: GPL 2+
Build system: r
Synopsis: Gradient-Based Coenospace Vegetation Simulator
Description:

Simulates the composition of samples of vegetation according to gradient-based vegetation theory. Features a flexible algorithm incorporating competition and complex multi-gradient interaction.

r-csclone 1.0
Propagated dependencies: r-moments@0.14.1 r-mcclust@1.0.1 r-lpsolve@5.6.23 r-dnacopy@1.84.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CSclone
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Nonparametric Modeling in R
Description:

Germline and somatic locus data which contain the total read depth and B allele read depth using Bayesian model (Dirichlet Process) to cluster. Meanwhile, the cluster model can deal with the SNVs mutation and the CNAs mutation.

r-cchs 0.4.5
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cchs
Licenses: GPL 3
Build system: r
Synopsis: Cox Model for Case-Cohort Data with Stratified Subcohort-Selection
Description:

This package contains a function, also called cchs', that calculates Estimator III of Borgan et al (2000), <DOI:10.1023/A:1009661900674>. This estimator is for fitting a Cox proportional hazards model to data from a case-cohort study where the subcohort was selected by stratified simple random sampling.

r-campsis 1.8.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-progressr@0.18.0 r-mass@7.3-65 r-jsonvalidate@1.5.0 r-jsonlite@2.0.0 r-ggplot2@4.0.1 r-future@1.68.0 r-furrr@0.3.1 r-dplyr@1.1.4 r-digest@0.6.39 r-campsismod@1.3.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/Calvagone/campsis
Licenses: GPL 3+
Build system: r
Synopsis: Generic PK/PD Simulation Platform Campsis
Description:

This package provides a generic, easy-to-use and intuitive pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on the R packages rxode2 and mrgsolve'. Campsis provides an abstraction layer over the underlying processes of defining a PK/PD model, assembling a custom dataset and running a simulation. The package has a strong dependency on the R package campsismod', which allows models to be read from and written to files, including through a JSON-based interface, and to be adapted further on the fly in the R environment. In addition, campsis allows users to assemble datasets in an intuitive manner, including via a JSON-based interface to import Campsis datasets defined using formal JSON schemas distributed with the package. Once the dataset is ready, the package prepares the simulation, calls rxode2 or mrgsolve (at the user's choice), and returns the results for the given model, dataset and desired simulation settings. The package itself is licensed under the GPL (>= 3); the JSON schema files shipped in inst/extdata are licensed separately under the Creative Commons Attribution 4.0 International (CC BY 4.0).

r-cmsafvis 1.3.0
Propagated dependencies: r-sp@2.2-0 r-sf@1.0-23 r-rcolorbrewer@1.1-3 r-rastervis@0.51.7 r-raster@3.6-32 r-progress@1.2.3 r-png@0.1-8 r-ncdf4@1.24 r-maps@3.4.3 r-mapproj@1.2.12 r-gridextra@2.3 r-fields@17.1 r-countrycode@1.6.1 r-colorspace@2.1-2 r-cmsafops@1.4.3 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cmsafvis
Licenses: GPL 3+
Build system: r
Synopsis: Tools to Visualize CM SAF NetCDF Data
Description:

The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<https://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The cmsafvis R-package provides a collection of R-operators for the analysis and visualization of CM SAF NetCDF data. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).

r-colorfast 1.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/coolbutuseless/colorfast
Licenses: Expat
Build system: r
Synopsis: Fast Conversion of R Colors to Color Component Values and Native Packed Integer Format
Description:

Color values in R are often represented as strings of hexadecimal colors or named colors. This package offers fast conversion of these color representations to either an array of red/green/blue/alpha values or to the packed integer format used in native raster objects. Functions for conversion are also exported at the C level for use in other packages. This fast conversion of colors is implemented using an order-preserving minimal perfect hash derived from Majewski et al (1996) "A Family of Perfect Hashing Methods" <doi:10.1093/comjnl/39.6.547>.

r-cadftest 0.3-3
Propagated dependencies: r-urca@1.3-4 r-tseries@0.10-58 r-sandwich@3.1-1 r-dynlm@0.3-6
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://www.jstatsoft.org/v32/i02
Licenses: GPL 2+
Build system: r
Synopsis: Package to Perform Covariate Augmented Dickey-Fuller Unit Root Tests
Description:

Hansen's (1995) Covariate-Augmented Dickey-Fuller (CADF) test. The only required argument is y, the Tx1 time series to be tested. If no stationary covariate X is passed to the procedure, then an ordinary ADF test is performed. The p-values of the test are computed using the procedure illustrated in Lupi (2009).

r-clustra 0.2.1
Propagated dependencies: r-mixsim@1.1-8 r-mgcv@1.9-4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clustra
Licenses: FSDG-compatible
Build system: r
Synopsis: Clustering Longitudinal Trajectories
Description:

Clusters longitudinal trajectories over time (can be unequally spaced, unequal length time series and/or partially overlapping series) on a common time axis. Performs k-means clustering on a single continuous variable measured over time, where each mean is defined by a thin plate spline fit to all points in a cluster. Distance is MSE across trajectory points to cluster spline. Provides graphs of derived cluster splines, silhouette plots, and Adjusted Rand Index evaluations of the number of clusters. Scales well to large data with multicore parallelism available to speed computation.

r-ctashiny 0.1.0
Propagated dependencies: r-shinymatrix@0.8.0 r-shiny@1.11.1 r-rpivottable@0.3.0 r-epitools@0.5-10.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CTAShiny
Licenses: GPL 2
Build system: r
Synopsis: Interactive Application for Working with Contingency Tables
Description:

An interactive application for working with contingency Tables. The application has a template for solving contingency table problems like chisquare test of independence,association plot between two categorical variables. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/CategoricalDataAnalysis/>.

r-connectednessapproach 1.0.4
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-urca@1.3-4 r-rugarch@1.5-4 r-rmgarch@1.4-2 r-riskparityportfolio@0.2.2 r-quantreg@6.1 r-progress@1.2.3 r-performanceanalytics@2.0.8 r-moments@0.14.1 r-mass@7.3-65 r-l1pack@0.62 r-igraph@2.2.1 r-glmnet@4.1-10 r-frequencyconnectedness@0.2.4 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ConnectednessApproach
Licenses: GPL 3
Build system: r
Synopsis: Connectedness Approach
Description:

The estimation of static and dynamic connectedness measures is created in a modular and user-friendly way. Besides, the time domain connectedness approaches, this package further allows to estimate the frequency connectedness approach, the joint spillover index and the extended joint connectedness approach. In addition, all connectedness frameworks can be based upon orthogonalized and generalized VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR and TVP-VAR models. Furthermore, the package includes the conditional, decomposed and partial connectedness measures as well as the pairwise connectedness index, influence index and corrected total connectedness index. Finally, a battery of datasets are available allowing to replicate a variety of connectedness papers.

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Total results: 68655