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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-condindtests 0.1.5
Propagated dependencies: r-rptests@0.1.5 r-randomforest@4.7-1.2 r-quantregforest@1.3-7.1 r-pracma@2.4.6 r-mize@0.2.5 r-mgcv@1.9-4 r-mass@7.3-65 r-lawstat@3.6 r-kernlab@0.9-33 r-catools@1.18.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/christinaheinze/nonlinearICP-and-CondIndTests
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Nonlinear Conditional Independence Tests
Description:

Code for a variety of nonlinear conditional independence tests: Kernel conditional independence test (Zhang et al., UAI 2011, <arXiv:1202.3775>), Residual Prediction test (based on Shah and Buehlmann, <arXiv:1511.03334>), Invariant environment prediction, Invariant target prediction, Invariant residual distribution test, Invariant conditional quantile prediction (all from Heinze-Deml et al., <arXiv:1706.08576>).

r-ctost 1.0.1
Propagated dependencies: r-rmarkdown@2.30 r-powertost@1.5-7 r-knitr@1.50 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/yboulag/cTOST
Licenses: AGPL 3
Build system: r
Synopsis: Finite Sample Correction of the Two One-Sided Tests in the Univariate Framework
Description:

This package provides a system containing easy-to-use tools to compute the bioequivalence assessment in the univariate framework using the methods proposed in Boulaguiem et al. (2023) <doi:10.1101/2023.03.11.532179>.

r-covidnor 2023.05.18
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.csids.no/covidnor/
Licenses: Expat
Build system: r
Synopsis: Public COVID-19 Data for Norway
Description:

Publicly available COVID-19 data for Norway cleaned and merged into one dataset, including PCR confirmed cases, tests, hospitalisation and vaccination.

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-cofast 0.2.0
Propagated dependencies: r-seurat@5.3.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-progress@1.2.3 r-profast@1.7 r-precast@1.8 r-pbapply@1.7-4 r-matrix@1.7-4 r-irlba@2.3.5.1 r-ggplot2@4.0.1 r-future@1.68.0 r-furrr@0.3.1 r-dr-sc@3.7 r-dplyr@1.1.4 r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/feiyoung/coFAST
Licenses: GPL 3
Build system: r
Synopsis: Spatially-Aware Cell Clustering Algorithm with Cluster Significant Assessment
Description:

This package provides a spatially-aware cell clustering algorithm is provided with cluster significance assessment. It comprises four key modules: spatially-aware cell-gene co-embedding, cell clustering, signature gene identification, and cluster significant assessment. More details can be referred to Peng Xie, et al. (2025) <doi:10.1016/j.cell.2025.05.035>.

r-clustimpute 0.2.4
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-magrittr@2.0.4 r-knitr@1.50 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-copula@1.1-6 r-clusterr@1.3.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ClustImpute
Licenses: GPL 3
Build system: r
Synopsis: K-Means Clustering with Build-in Missing Data Imputation
Description:

This k-means algorithm is able to cluster data with missing values and as a by-product completes the data set. The implementation can deal with missing values in multiple variables and is computationally efficient since it iteratively uses the current cluster assignment to define a plausible distribution for missing value imputation. Weights are used to shrink early random draws for missing values (i.e., draws based on the cluster assignments after few iterations) towards the global mean of each feature. This shrinkage slowly fades out after a fixed number of iterations to reflect the increasing credibility of cluster assignments. See the vignette for details.

r-cppdoubles 0.4.0
Propagated dependencies: r-cpp11@0.5.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cppdoubles
Licenses: Expat
Build system: r
Synopsis: Fast Relative Comparisons of Floating Point Numbers in 'C++'
Description:

Compare double-precision floating point vectors using relative differences. All equality operations are calculated using cpp11'.

r-clap 0.1.0
Propagated dependencies: r-rlang@1.1.6 r-mclust@6.1.2 r-fnn@1.1.4.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/pridiltal/clap
Licenses: GPL 3
Build system: r
Synopsis: Detecting Class Overlapping Regions in Multidimensional Data
Description:

The issue of overlapping regions in multidimensional data arises when different classes or clusters share similar feature representations, making it challenging to delineate distinct boundaries between them accurately. This package provides methods for detecting and visualizing these overlapping regions using partitional clustering techniques based on nearest neighbor distances.

r-corncob 0.4.2
Propagated dependencies: r-vgam@1.1-13 r-trust@0.1-8 r-scales@1.4.0 r-rlang@1.1.6 r-numderiv@2016.8-1.1 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-detectseparation@0.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/statdivlab/corncob
Licenses: GPL 2+
Build system: r
Synopsis: Count Regression for Correlated Observations with the Beta-Binomial
Description:

Statistical modeling for correlated count data using the beta-binomial distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.

r-colormap 0.1.4
Propagated dependencies: r-v8@8.0.1 r-stringr@1.6.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/bhaskarvk/colormap
Licenses: Expat
Build system: r
Synopsis: Color Palettes using Colormaps Node Module
Description:

Allows to generate colors from palettes defined in the colormap module of Node.js'. (see <https://github.com/bpostlethwaite/colormap> for more information). In total it provides 44 distinct palettes made from sequential and/or diverging colors. In addition to the pre defined palettes you can also specify your own set of colors. There are also scale functions that can be used with ggplot2'.

r-ciu 0.8
Propagated dependencies: r-rcpp@1.1.0 r-ggplot2@4.0.1 r-ggbeeswarm@0.7.2 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ciu
Licenses: Expat
Build system: r
Synopsis: Contextual Importance and Utility
Description:

Implementation of the Contextual Importance and Utility (CIU) concepts for Explainable AI (XAI). A description of CIU can be found in e.g. Främling (2020) <doi:10.1007/978-3-030-51924-7_4>.

r-cvmaplfam 0.1.1
Propagated dependencies: r-quadprog@1.5-8 r-mgcv@1.9-4 r-mass@7.3-65 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cvmaPLFAM
Licenses: GPL 3+
Build system: r
Synopsis: Cross-Validation Model Averaging for Partial Linear Functional Additive Models
Description:

Produce an averaging estimate/prediction by combining all candidate models for partial linear functional additive models, using multi-fold cross-validation criterion. More details can be referred to arXiv e-Prints via <doi:10.48550/arXiv.2105.00966>.

r-coxrobust 1.0.2
Propagated dependencies: r-survival@3.8-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/ShanaScogin/coxrobust
Licenses: GPL 3
Build system: r
Synopsis: Fit Robustly Proportional Hazards Regression Model
Description:

An implementation of robust estimation in Cox model. Functionality includes fitting efficiently and robustly Cox proportional hazards regression model in its basic form, where explanatory variables are time independent with one event per subject. Method is based on a smooth modification of the partial likelihood.

r-comire 0.8
Propagated dependencies: r-truncnorm@1.0-9 r-splines2@0.5.4 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-kernsmooth@2.23-26 r-gtools@3.9.5 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=CoMiRe
Licenses: GPL 2
Build system: r
Synopsis: Convex Mixture Regression
Description:

Posterior inference under the convex mixture regression (CoMiRe) models introduced by Canale, Durante, and Dunson (2018) <doi:10.1111/biom.12917>.

r-cggp 1.0.4
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/CollinErickson/CGGP
Licenses: GPL 3
Build system: r
Synopsis: Composite Grid Gaussian Processes
Description:

Run computer experiments using the adaptive composite grid algorithm with a Gaussian process model. The algorithm works best when running an experiment that can evaluate thousands of points from a deterministic computer simulation. This package is an implementation of a forthcoming paper by Plumlee, Erickson, Ankenman, et al. For a preprint of the paper, contact the maintainer of this package.

r-cgaim 1.0.3
Propagated dependencies: r-truncatednormal@2.3 r-scar@0.2-2 r-scam@1.2-21 r-quadprog@1.5-8 r-osqp@0.6.3.3 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-limsolve@2.0.1 r-gratia@0.11.2 r-foreach@1.5.2 r-doparallel@1.0.17 r-coneproj@1.23 r-cgam@1.31
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/PierreMasselot/cgaim
Licenses: GPL 3
Build system: r
Synopsis: Constrained Groupwise Additive Index Models
Description:

Fits constrained groupwise additive index models and provides functions for inference and interpretation of these models. The method is described in Masselot, Chebana, Campagna, Lavigne, Ouarda, Gosselin (2022) "Constrained groupwise additive index models" <doi:10.1093/biostatistics/kxac023>.

r-comparecausalnetworks 0.2.6.2
Propagated dependencies: r-matrix@1.7-4 r-expm@1.0-0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/christinaheinze/CompareCausalNetworks
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Interface to Diverse Estimation Methods of Causal Networks
Description:

Unified interface for the estimation of causal networks, including the methods backShift (from package backShift'), bivariateANM (bivariate additive noise model), bivariateCAM (bivariate causal additive model), CAM (causal additive model) (from package CAM'; the package is temporarily unavailable on the CRAN repository; formerly available versions can be obtained from the archive), hiddenICP (invariant causal prediction with hidden variables), ICP (invariant causal prediction) (from package InvariantCausalPrediction'), GES (greedy equivalence search), GIES (greedy interventional equivalence search), LINGAM', PC (PC Algorithm), FCI (fast causal inference), RFCI (really fast causal inference) (all from package pcalg') and regression.

r-causalot 1.0.2
Propagated dependencies: r-torch@0.16.3 r-sandwich@3.1-1 r-rlang@1.1.6 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-r6@2.6.1 r-osqp@0.6.3.3 r-matrixstats@1.5.0 r-matrix@1.7-4 r-loo@2.8.0 r-lbfgsb3c@2024-3.5 r-ggplot2@4.0.1 r-cbps@0.24 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=causalOT
Licenses: FSDG-compatible
Build system: r
Synopsis: Optimal Transport Weights for Causal Inference
Description:

Uses optimal transport distances to find probabilistic matching estimators for causal inference. These methods are described in Dunipace, Eric (2021) <arXiv:2109.01991>. The package will build the weights, estimate treatment effects, and calculate confidence intervals via the methods described in the paper. The package also supports several other methods as described in the help files.

r-clttools 1.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clttools
Licenses: GPL 2
Build system: r
Synopsis: Central Limit Theorem Experiments (Theoretical and Simulation)
Description:

Central limit theorem experiments presented by data frames or plots. Functions include generating theoretical sample space, corresponding probability, and simulated results as well.

r-chor 0.0-4
Dependencies: openjdk@25
Propagated dependencies: r-rjava@1.0-11 r-commonsmath@1.2.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ChoR
Licenses: GPL 3
Build system: r
Synopsis: Chordalysis R Package
Description:

Learning the structure of graphical models from datasets with thousands of variables. More information about the research papers detailing the theory behind Chordalysis is available at <http://www.francois-petitjean.com/Research> (KDD 2016, SDM 2015, ICDM 2014, ICDM 2013). The R package development site is <https://github.com/HerrmannM/Monash-ChoR>.

r-coxerr 1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=coxerr
Licenses: GPL 2+
Build system: r
Synopsis: Cox Regression with Dependent Error in Covariates
Description:

Perform the functional modeling methods of Huang and Wang (2018) <doi:10.1111/biom.12741> to accommodate dependent error in covariates of the proportional hazards model. The adopted measurement error model has minimal assumptions on the dependence structure, and an instrumental variable is supposed to be available.

r-covid19dbcand 0.1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/MohammedFCIS/covid19dbcand
Licenses: CC0
Build system: r
Synopsis: Selected 'Drugbank' Drugs for COVID-19 Treatment Related Data in R Format
Description:

This package provides different datasets parsed from Drugbank <https://www.drugbank.ca/covid-19> database using dbparser package. It is a smaller version from dbdataset package. It contains only information about COVID-19 possible treatment.

r-cond 1.2-4
Propagated dependencies: r-survival@3.8-3 r-statmod@1.5.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.r-project.org
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Approximate Conditional Inference for Logistic and Loglinear Models
Description:

This package implements higher order likelihood-based inference for logistic and loglinear models.

r-coxr2 1.0
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=CoxR2
Licenses: GPL 2
Build system: r
Synopsis: R-Squared Measure Based on Partial LR Statistic, for the Cox PH Regression Model
Description:

Calculate the R-squared, aka explained randomness, based on the partial likelihood ratio statistic under the Cox Proportional Hazard model [J O'Quigley, R Xu, J Stare (2005) <doi:10.1002/sim.1946>].

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