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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-covsim 1.1.0
Propagated dependencies: r-tmvtnorm@1.7 r-rvinecopulib@0.7.3.1.0 r-pearsonds@1.3.2 r-nleqslv@3.3.5 r-matrix@1.7-4 r-mass@7.3-65 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=covsim
Licenses: GPL 2+
Build system: r
Synopsis: VITA, IG and PLSIM Simulation for Given Covariance and Marginals
Description:

Random sampling from distributions with user-specified population covariance matrix. Marginal information may be fully specified, for which the package implements the VITA (VIne-To-Anything) algorithm Grønneberg and Foldnes (2017) <doi:10.1007/s11336-017-9569-6>. See also Grønneberg, Foldnes and Marcoulides (2022) <doi:10.18637/jss.v102.i03>. Alternatively, marginal skewness and kurtosis may be specified, for which the package implements the IG (independent generator) and PLSIM (piecewise linear) algorithms, see Foldnes and Olsson (2016) <doi:10.1080/00273171.2015.1133274> and Foldnes and Grønneberg (2021) <doi:10.1080/10705511.2021.1949323>, respectively.

r-coresim 0.2.4
Propagated dependencies: r-mass@7.3-65 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=coreSim
Licenses: GPL 3+
Build system: r
Synopsis: Core Functionality for Simulating Quantities of Interest from Generalised Linear Models
Description:

Core functions for simulating quantities of interest from generalised linear models (GLM). This package will form the backbone of a series of other packages that improve the interpretation of GLM estimates.

r-cure 1.1.1
Propagated dependencies: r-survival@3.8-3 r-statmod@1.5.1 r-rstpm2@1.7.1 r-reshape2@1.4.5 r-relsurv@2.3-3 r-numderiv@2016.8-1.1 r-date@1.2-43
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/LasseHjort/cuRe
Licenses: GPL 2+
Build system: r
Synopsis: Parametric Cure Model Estimation
Description:

This package contains functions for estimating generalized parametric mixture and non-mixture cure models <doi:10.1016/j.cmpb.2022.107125>, loss of lifetime, mean residual lifetime, and crude event probabilities.

r-connector-databricks 0.1.0
Propagated dependencies: r-zephyr@0.1.3 r-withr@3.0.2 r-rlang@1.1.6 r-r6@2.6.1 r-purrr@1.2.0 r-odbc@1.6.4.1 r-hms@1.1.4 r-fs@1.6.6 r-dplyr@1.1.4 r-dbplyr@2.5.1 r-dbi@1.2.3 r-connector@1.0.0 r-cli@3.6.5 r-checkmate@2.3.3 r-brickster@0.2.12 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://novonordisk-opensource.github.io/connector.databricks/
Licenses: FSDG-compatible
Build system: r
Synopsis: Expand 'connector' Package for 'Databricks' Tables and Volumes
Description:

Expands the connector <https://github.com/NovoNordisk-OpenSource/connector> package and provides a convenient interface for accessing and interacting with Databricks <https://www.databricks.com> volumes and tables directly from R.

r-clarify 0.2.2
Propagated dependencies: r-rlang@1.1.6 r-pbapply@1.7-4 r-marginaleffects@0.31.0 r-insight@1.4.3 r-ggplot2@4.0.1 r-chk@0.10.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/iqss/clarify
Licenses: GPL 3+
Build system: r
Synopsis: Simulation-Based Inference for Regression Models
Description:

This package performs simulation-based inference as an alternative to the delta method for obtaining valid confidence intervals and p-values for regression post-estimation quantities, such as average marginal effects and predictions at representative values. This framework for simulation-based inference is especially useful when the resulting quantity is not normally distributed and the delta method approximation fails. The methodology is described in Greifer, et al. (2025) <doi:10.32614/RJ-2024-015>. clarify is meant to replace some of the functionality of the archived package Zelig'; see the vignette "Translating Zelig to clarify" for replicating this functionality.

r-clusterability 0.2.2.0
Propagated dependencies: r-sparsepca@0.1.2 r-elasticnet@1.3 r-diptest@0.77-2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clusterability
Licenses: GPL 2
Build system: r
Synopsis: Performs Tests for Cluster Tendency of a Data Set
Description:

Test for cluster tendency (clusterability) of a data set. The methods implemented - reducing the data set to a single dimension using principal component analysis or computing pairwise distances, and performing a multimodality test like the Dip Test or Silverman's Critical Bandwidth Test - are described in Adolfsson, Ackerman, and Brownstein (2019) <doi:10.1016/j.patcog.2018.10.026>. Such methods can inform whether clustering algorithms are appropriate for a data set.

r-comradesm 0.1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ComradesM
Licenses: GPL 2+
Build system: r
Synopsis: The Comrades Marathon 1921 to 2019
Description:

Datasets related to the Comrades Marathon used in the book Antony Unwin (2024, ISBN:978-0367674007) "Getting (more out of) Graphics". The main dataset contains the times of every runner that finished in the time limit for each year the race was run.

r-conformalinference-multi 1.1.2
Propagated dependencies: r-gridextra@2.3 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/ryantibs/conformal
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Conformal Inference Tools for Regression with Multivariate Response
Description:

It computes full conformal, split conformal and multi-split conformal prediction regions when the response variable is multivariate (i.e. dimension is greater than one). Moreover, the package also contains plot functions to visualize the output of the full and split conformal functions. To guarantee consistency, the package structure mimics the univariate package conformalInference by Ryan Tibshirani. See Lei, Gâ sell, Rinaldo, Tibshirani, & Wasserman (2018) <doi:10.1080/01621459.2017.1307116> for full and split conformal prediction in regression, and Barber, Candès, Ramdas, & Tibshirani (2023) <doi:10.1214/23-AOS2276> for extensions beyond exchangeability.

r-cipostselect 0.2.2
Propagated dependencies: r-tictoc@1.2.1 r-mlbench@2.1-6 r-mass@7.3-65 r-magrittr@2.0.4 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/Diallo0/CIpostSelect
Licenses: Expat
Build system: r
Synopsis: Confidence Interval Post-Selection of Variable
Description:

Calculates confidence intervals after variable selection using repeated data splits. The package offers methods to address the challenges of post-selection inference, ensuring more accurate confidence intervals in models involving variable selection. The two main functions are lmps', which records the different models selected across multiple data splits as well as the corresponding coefficient estimates, and cips', which takes the lmps object as input to select variables and perform inferences using two types of voting.

r-cnbdistr 1.0.1
Propagated dependencies: r-hypergeo@1.2-14
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cnbdistr
Licenses: GPL 3
Build system: r
Synopsis: Conditional Negative Binomial Distribution
Description:

Provided R functions for working with the Conditional Negative Binomial distribution.

r-clustcr2 1.7.3.01
Propagated dependencies: r-vlf@1.1-3 r-stringr@1.6.0 r-sna@2.8 r-scales@1.4.0 r-rcolorbrewer@1.1-3 r-plyr@1.8.9 r-network@1.19.0 r-ggseqlogo@0.2 r-ggplot2@4.0.1 r-desctools@0.99.60
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ClusTCR2
Licenses: GPL 3+
Build system: r
Synopsis: Identifying Similar T Cell Receptor Hyper-Variable Sequences with 'ClusTCR2'
Description:

Enhancing T cell receptor (TCR) sequence analysis, ClusTCR2', based on ClusTCR python program, leverages Hamming distance to compare the complement-determining region three (CDR3) sequences for sequence similarity, variable gene (V gene) and length. The second step employs the Markov Cluster Algorithm to identify clusters within an undirected graph, providing a summary of amino acid motifs and matrix for generating network plots. Tailored for single-cell RNA-seq data with integrated TCR-seq information, ClusTCR2 is integrated into the Single Cell TCR and Expression Grouped Ontologies (STEGO) R application or STEGO.R'. See the two publications for more details. Sebastiaan Valkiers, Max Van Houcke, Kris Laukens, Pieter Meysman (2021) <doi:10.1093/bioinformatics/btab446>, Kerry A. Mullan, My Ha, Sebastiaan Valkiers, Nicky de Vrij, Benson Ogunjimi, Kris Laukens, Pieter Meysman (2023) <doi:10.1101/2023.09.27.559702>.

r-codez 1.0.0
Propagated dependencies: r-tictoc@1.2.1 r-tensorflow@2.20.0 r-scales@1.4.0 r-readr@2.1.6 r-purrr@1.2.0 r-philentropy@0.10.0 r-narray@0.5.2 r-moments@0.14.1 r-modeest@2.4.0 r-lubridate@1.9.4 r-keras@2.16.1 r-imputets@3.4 r-greybox@2.0.8 r-ggplot2@4.0.1 r-fastdummies@1.7.5 r-fancova@0.6-1 r-entropy@1.3.2 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://rpubs.com/giancarlo_vercellino/codez
Licenses: GPL 3
Build system: r
Synopsis: Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on Tensorflow
Description:

Proposes Seq2seq Time-Feature Analysis using an Encoder-Decoder to project into latent space and a Forward Network to predict the next sequence.

r-comperes 0.2.7
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/echasnovski/comperes
Licenses: Expat
Build system: r
Synopsis: Manage Competition Results
Description:

This package provides tools for storing and managing competition results. Competition is understood as a set of games in which players gain some abstract scores. There are two ways for storing results: in long (one row per game-player) and wide (one row per game with fixed amount of players) formats. This package provides functions for creation and conversion between them. Also there are functions for computing their summary and Head-to-Head values for players. They leverage grammar of data manipulation from dplyr'.

r-completejourney 1.1.1
Propagated dependencies: r-zeallot@0.2.0 r-tibble@3.3.0 r-stringr@1.6.0 r-progress@1.2.3 r-dplyr@1.1.4 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/bradleyboehmke/completejourney
Licenses: CC0
Build system: r
Synopsis: Retail Shopping Data
Description:

Retail shopping transactions for 2,469 households over one year. Originates from the 84.51° Complete Journey 2.0 source files <https://www.8451.com/area51> which also includes useful metadata on products, coupons, campaigns, and promotions.

r-crossclustering 4.1.3
Propagated dependencies: r-purrr@1.2.0 r-mclust@6.1.2 r-flip@2.5.1 r-dplyr@1.1.4 r-crayon@1.5.3 r-cluster@2.1.8.1 r-cli@3.6.5 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://CRAN.R-project.org/package=CrossClustering
Licenses: GPL 3
Build system: r
Synopsis: Partial Clustering Algorithm
Description:

Provide the CrossClustering algorithm (Tellaroli et al. (2016) <doi:10.1371/journal.pone.0152333>), which is a partial clustering algorithm that combines the Ward's minimum variance and Complete Linkage algorithms, providing automatic estimation of a suitable number of clusters and identification of outlier elements.

r-corpora 0.7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://SIGIL.R-Forge.R-Project.org/
Licenses: GPL 3
Build system: r
Synopsis: Statistics and Data Sets for Corpus Frequency Data
Description:

Utility functions for the statistical analysis of corpus frequency data. This package is a companion to the open-source course "Statistical Inference: A Gentle Introduction for Computational Linguists and Similar Creatures" ('SIGIL').

r-cifmodeling 0.9.8
Propagated dependencies: r-scales@1.4.0 r-rcpp@1.1.0 r-patchwork@1.3.2 r-nleqslv@3.3.5 r-lifecycle@1.0.4 r-ggsurvfit@1.2.0 r-ggplot2@4.0.1 r-generics@0.1.4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://gestimation.github.io/cifmodeling/
Licenses: Expat
Build system: r
Synopsis: Visualization and Polytomous Modeling of Survival and Competing Risks
Description:

This package provides a publication-ready toolkit for modern survival and competing risks analysis with a minimal, formula-based interface. Both nonparametric estimation and direct polytomous regression of cumulative incidence functions (CIFs) are supported. The main functions cifcurve()', cifplot()', and cifpanel() estimate survival and CIF curves and produce high-quality graphics with risk tables, censoring and competing-risk marks, and multi-panel or inset layouts built on ggplot2 and ggsurvfit'. The modeling function polyreg() performs direct polytomous regression for coherent joint modeling of all cause-specific CIFs to estimate risk ratios, odds ratios, or subdistribution hazard ratios at user-specified time points. All core functions adopt a formula-and-data syntax and return tidy and extensible outputs that integrate smoothly with modelsummary', broom', and the broader tidyverse ecosystem. Key numerical routines are implemented in C++ via Rcpp'.

r-cequre 1.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cequre
Licenses: GPL 2+
Build system: r
Synopsis: Censored Quantile Regression & Monotonicity-Respecting Restoring
Description:

Perform censored quantile regression of Huang (2010) <doi:10.1214/09-AOS771>, and restore monotonicity respecting via adaptive interpolation for dynamic regression of Huang (2017) <doi:10.1080/01621459.2016.1149070>. The monotonicity-respecting restoration applies to general dynamic regression models including (uncensored or censored) quantile regression model, additive hazards model, and dynamic survival models of Peng and Huang (2007) <doi:10.1093/biomet/asm058>, among others.

r-concordance 2.0.0
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-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=concordance
Licenses: GPL 2
Build system: r
Synopsis: Product Concordance
Description:

This package provides a set of utilities for matching products in different classification codes used in international trade research. It supports concordance between the Harmonized System (HS0, HS1, HS2, HS3, HS4, HS5, HS combined), the Standard International Trade Classification (SITC1, SITC2, SITC3, SITC4), the North American Industry Classification System (NAICS combined), as well as the Broad Economic Categories (BEC), the International Standard of Industrial Classification (ISIC), and the Standard Industrial Classification (SIC). It also provides code nomenclature/descriptions look-up, Rauch classification look-up (via concordance to SITC2), and trade elasticity look-up (via concordance to HS0 or SITC3 codes).

r-compindpca 0.1.0
Propagated dependencies: r-factoextra@1.0.7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=compindPCA
Licenses: GPL 3
Build system: r
Synopsis: Computation of Relative Weights of Variables and Composite Index Values Based on PCA
Description:

It helps in development of a principal component analysis based composite index by assigning weights to variables and combining the weighted variables. For method details see Sendhil, R., Jha, A., Kumar, A. and Singh, S. (2018). <doi:10.1016/j.ecolind.2018.02.053>, and Wu, T. (2021). <doi:10.1016/j.ecolind.2021.108006>.

r-calibrationcurves 3.0.0
Propagated dependencies: r-zoo@1.8-14 r-timeroc@0.4 r-survival@3.8-3 r-rstudioapi@0.17.1 r-rms@8.1-0 r-riskregression@2026.02.13 r-metafor@4.8-0 r-meta@8.2-1 r-mertools@0.6.4 r-magrittr@2.0.4 r-lme4@1.1-37 r-hmisc@5.2-4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-bookdown@0.45
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://bavodc.github.io/websiteCalibrationCurves/
Licenses: GPL 3+
Build system: r
Synopsis: Calibration Performance
Description:

Plots calibration curves and computes statistics for assessing calibration performance. See Lasai et al. (2025) <doi:10.48550/arXiv.2503.08389>, De Cock Campo (2023) <doi:10.48550/arXiv.2309.08559> and Van Calster et al. (2016) <doi:10.1016/j.jclinepi.2015.12.005>.

r-cellvolumedist 1.5
Propagated dependencies: r-minpack-lm@1.2-4 r-gplots@3.2.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cellVolumeDist
Licenses: GPL 2+
Build system: r
Synopsis: Functions to Fit Cell Volume Distributions and Thereby Estimate Cell Growth Rates and Division Times
Description:

This package implements a methodology for using cell volume distributions to estimate cell growth rates and division times that is described in the paper, "Cell Volume Distributions Reveal Cell Growth Rates and Division Times", by Michael Halter, John T. Elliott, Joseph B. Hubbard, Alessandro Tona and Anne L. Plant, which appeared in the Journal of Theoretical Biology. In order to reproduce the analysis used to obtain Table 1 in the paper, execute the command "example(fitVolDist)".

r-clear 0.0.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/joundso/cleaR
Licenses: GPL 3
Build system: r
Synopsis: Clean the R Console and Environment
Description:

Small package to clean the R console and the R environment with the call of just one function.

r-causaleffect 1.3.15
Propagated dependencies: r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/santikka/causaleffect/
Licenses: GPL 2+
Build system: r
Synopsis: Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models
Description:

This package provides functions for identification and transportation of causal effects. Provides a conditional causal effect identification algorithm (IDC) by Shpitser, I. and Pearl, J. (2006) <http://ftp.cs.ucla.edu/pub/stat_ser/r329-uai.pdf>, an algorithm for transportability from multiple domains with limited experiments by Bareinboim, E. and Pearl, J. (2014) <http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>, and a selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015) <http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>. All of the previously mentioned algorithms are based on a causal effect identification algorithm by Tian , J. (2002) <http://ftp.cs.ucla.edu/pub/stat_ser/r309.pdf>.

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