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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-crumble 0.1.2
Propagated dependencies: r-torch@0.16.3 r-s7@0.2.1 r-rsymphony@0.1-33 r-purrr@1.2.0 r-progressr@0.18.0 r-origami@1.0.7 r-mlr3superlearner@0.1.2 r-matrix@1.7-4 r-lmtp@1.5.3 r-ife@0.2.3 r-generics@0.1.4 r-data-table@1.17.8 r-coro@1.1.0 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=crumble
Licenses: GPL 3+
Build system: r
Synopsis: Flexible and General Mediation Analysis Using Riesz Representers
Description:

This package implements a modern, unified estimation strategy for common mediation estimands (natural effects, organic effects, interventional effects, and recanting twins) in combination with modified treatment policies as described in Liu, Williams, Rudolph, and DÃ az (2024) <doi:10.48550/arXiv.2408.14620>. Estimation makes use of recent advancements in Riesz-learning to estimate a set of required nuisance parameters with deep learning. The result is the capability to estimate mediation effects with binary, categorical, continuous, or multivariate exposures with high-dimensional mediators and mediator-outcome confounders using machine learning.

r-compute-es 0.2-6
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://acdelre.github.io/apps/compute_es/
Licenses: GPL 2
Build system: r
Synopsis: Compute Effect Sizes
Description:

Several functions are available for calculating the most widely used effect sizes (ES), along with their variances, confidence intervals and p-values. The output includes ES's of d (mean difference), g (unbiased estimate of d), r (correlation coefficient), z (Fisher's z), and OR (odds ratio and log odds ratio). In addition, NNT (number needed to treat), U3, CLES (Common Language Effect Size) and Cliff's Delta are computed. This package uses recommended formulas as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009). A free web application is available at <https://acdelre.github.io/apps/compute_es/>.

r-condoroptions 1.0.1
Propagated dependencies: r-tibble@3.3.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 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=condorOptions
Licenses: GPL 3
Build system: r
Synopsis: Trading Condor Options Strategies
Description:

Trading of Condor Options Strategies is represented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. Guy Cohen (â The Bible of Options Strategies (2nd ed.)â , 2015, ISBN: 9780133964028). Zura Kakushadze, Juan A. Serur (â 151 Trading Strategiesâ , 2018, ISBN: 9783030027919). John C. Hull (â Options, Futures, and Other Derivatives (11th ed.)â , 2022, ISBN: 9780136939979).

r-curstatci 0.1.1
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/kimhendrickx/curstatCI
Licenses: GPL 3
Build system: r
Synopsis: Confidence Intervals for the Current Status Model
Description:

Computes the maximum likelihood estimator, the smoothed maximum likelihood estimator and pointwise bootstrap confidence intervals for the distribution function under current status data. Groeneboom and Hendrickx (2017) <doi:10.1214/17-EJS1345>.

r-cvap 0.1.6
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-fs@1.6.6 r-dplyr@1.1.4 r-cli@3.6.5 r-censable@0.0.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/christopherkenny/cvap
Licenses: Expat
Build system: r
Synopsis: Citizen Voting Age Population
Description:

Works with the Citizen Voting Age Population special tabulation from the US Census Bureau <https://www.census.gov/programs-surveys/decennial-census/about/voting-rights/cvap.html>. Provides tools to download and process raw data. Also provides a downloading interface to processed data. Implements a very basic approach to estimate block level citizen voting age population from block group data.

r-csv 0.6.2
Propagated dependencies: r-stringi@1.8.7 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=csv
Licenses: GPL 3
Build system: r
Synopsis: Read and Write CSV Files with Selected Conventions
Description:

Reads and writes CSV with selected conventions. Uses the same generic function for reading and writing to promote consistent formats.

r-clmplus 1.0.1
Propagated dependencies: r-stmomo@0.4.1 r-reshape2@1.4.5 r-gridextra@2.3 r-ggplot2@4.0.1 r-forecast@8.24.0 r-chainladder@0.2.20
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/gpitt71/clmplus
Licenses: GPL 2+
Build system: r
Synopsis: Tool-Box of Chain Ladder Plus Models
Description:

Implementation of the ageâ periodâ cohort models for claim development presented in Pittarello G, Hiabu M, Villegas A (2025) â Replicating and Extending Chainâ Ladder via an Ageâ Periodâ Cohort Structure on the Claim Development in a Runâ Off Triangleâ <doi:10.1080/10920277.2025.2496725>.

r-colorfindr 0.1.5
Propagated dependencies: r-treemap@2.4-4 r-tiff@0.1-12 r-tibble@3.3.0 r-stringr@1.6.0 r-rsvg@2.7.0 r-purrr@1.2.0 r-png@0.1-8 r-plotwidgets@0.5.1 r-plotly@4.11.0 r-pixmap@0.4-14 r-magrittr@2.0.4 r-jpeg@0.1-11 r-dplyr@1.1.4 r-bmp@0.3.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=colorfindr
Licenses: GPL 2+
Build system: r
Synopsis: Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format Images
Description:

Extracts colors from various image types, returns customized reports and plots treemaps and 3D scatterplots of image compositions. Color palettes can also be created.

r-connected 1.1
Propagated dependencies: r-reshape2@1.4.5 r-lfe@3.1.1 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://kwstat.github.io/connected/
Licenses: GPL 2+
Build system: r
Synopsis: Visualize and Improve Connectedness of Factors in Tables
Description:

Visualize the connectedness of factors in two-way tables. Perform two-way filtering to improve the degree of connectedness. See Weeks & Williams (1964) <doi:10.1080/00401706.1964.10490188>.

r-cgnm 0.9.3
Propagated dependencies: r-shiny@1.11.1 r-mass@7.3-65 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=CGNM
Licenses: Expat
Build system: r
Synopsis: Cluster Gauss-Newton Method
Description:

Find multiple solutions of a nonlinear least squares problem. Cluster Gauss-Newton method does not assume uniqueness of the solution of the nonlinear least squares problem and compute multiple minimizers. Please cite the following paper when this software is used in your research: Aoki et al. (2020) <doi:10.1007/s11081-020-09571-2>. Cluster Gaussâ Newton method. Optimization and Engineering, 1-31. Please cite the following paper when profile likelihood plot is drawn with this software and used in your research: Aoki and Sugiyama (2024) <doi:10.1002/psp4.13055>. Cluster Gauss-Newton method for a quick approximation of profile likelihood: With application to physiologically-based pharmacokinetic models. CPT Pharmacometrics Syst Pharmacol.13(1):54-67. GPT based helper bot available at <https://chatgpt.com/g/g-684936db9e748191a2796debb00cd755-cluster-gauss-newton-method-helper-bot> .

r-countsplit 4.0.0
Propagated dependencies: r-rcpp@1.1.0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/anna-neufeld/countsplit
Licenses: Expat
Build system: r
Synopsis: Splitting a Count Matrix into Independent Folds
Description:

This package implements the count splitting methodology from Neufeld et al. (2022) <doi:10.1093/biostatistics/kxac047> and Neufeld et al. (2023) <arXiv:2307.12985>. Intended for turning a matrix of single-cell RNA sequencing counts, or similar count datasets, into independent folds that can be used for training/testing or cross validation. Assumes that the entries in the matrix are from a Poisson or a negative binomial distribution.

r-clusterrepro 0.9
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.ncbi.nlm.nih.gov/pubmed/16613834.
Licenses: GPL 2
Build system: r
Synopsis: Reproducibility of Gene Expression Clusters
Description:

This is a function for validating microarray clusters via reproducibility, based on the paper referenced below.

r-cloneseeker 1.0.16
Propagated dependencies: r-quantmod@0.4.28 r-mc2d@0.2.1 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://oompa.r-forge.r-project.org/
Licenses: ASL 2.0
Build system: r
Synopsis: Seeking and Finding Clones in Copy Number and Sequencing Data
Description:

Defines the classes and functions used to simulate and to analyze data sets describing copy number variants and, optionally, sequencing mutations in order to detect clonal subsets. See Zucker et al. (2019) <doi:10.1093/bioinformatics/btz057>.

r-capitalr 1.3.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=capitalR
Licenses: GPL 3
Build system: r
Synopsis: Capital Budgeting Analysis, Annuity Loan Calculations and Amortization Schedules
Description:

This package provides Capital Budgeting Analysis functionality and the essential Annuity loan functions. Also computes Loan Amortization Schedules including schedules with irregular payments.

r-cbpe 0.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/mnrzrad/CBPE
Licenses: GPL 2+
Build system: r
Synopsis: Correlation-Based Penalized Estimators
Description:

This package provides correlation-based penalty estimators for both linear and logistic regression models by implementing a new regularization method that incorporates correlation structures within the data. This method encourages a grouping effect where strongly correlated predictors tend to be in or out of the model together. See Tutz and Ulbricht (2009) <doi:10.1007/s11222-008-9088-5> and Algamal and Lee (2015) <doi:10.1016/j.eswa.2015.08.016>.

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-crosswalkr 0.4.0
Propagated dependencies: r-tibble@3.3.0 r-readxl@1.4.5 r-readr@2.1.6 r-labelled@2.16.0 r-haven@2.5.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/btskinner/crosswalkr
Licenses: Expat
Build system: r
Synopsis: Rename and Encode Data Frames Using External Crosswalk Files
Description:

This package provides a pair of functions for renaming and encoding data frames using external crosswalk files. It is especially useful when constructing master data sets from multiple smaller data sets that do not name or encode variables consistently across files. Based on similar commands in Stata'.

r-contentid 0.0.19
Propagated dependencies: r-openssl@2.3.4 r-httr@1.4.7 r-fs@1.6.6 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/cboettig/contentid
Licenses: Expat
Build system: r
Synopsis: An Interface for Content-Based Identifiers
Description:

An interface for creating, registering, and resolving content-based identifiers for data management. Content-based identifiers rely on the cryptographic hashes to refer to the files they identify, thus, anyone possessing the file can compute the identifier using a well-known standard algorithm, such as SHA256'. By registering a URL at which the content is accessible to a public archive (such as Hash Archive) or depositing data in a scientific repository such Zenodo', DataONE or SoftwareHeritage', the content identifier can serve many functions typically associated with A Digital Object Identifier ('DOI'). Unlike location-based identifiers like DOIs', content-based identifiers permit the same content to be registered in many locations.

r-cohortsurvival 1.1.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-patientprofiles@1.4.5 r-omopgenerics@1.3.6 r-glue@1.8.0 r-dplyr@1.1.4 r-dbi@1.2.3 r-clock@0.7.3 r-cli@3.6.5 r-cdmconnector@2.3.0 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://darwin-eu-dev.github.io/CohortSurvival/
Licenses: FSDG-compatible
Build system: r
Synopsis: Estimate Survival from Common Data Model Cohorts
Description:

Estimate survival using data mapped to the Observational Medical Outcomes Partnership common data model. Survival can be estimated based on user-defined study cohorts.

r-ccweights 0.1.6
Propagated dependencies: r-shiny@1.11.1 r-rmarkdown@2.30 r-readxl@1.4.5 r-readr@2.1.6 r-plotly@4.11.0 r-magrittr@2.0.4 r-fresh@0.2.2 r-dt@0.34.0 r-dplyr@1.1.4 r-bs4dash@2.3.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CCWeights
Licenses: GPL 3
Build system: r
Synopsis: Perform Weighted Linear Regression for Calibration Curve
Description:

Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. In addition, a shiny App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.

r-chmm 0.1.1
Propagated dependencies: r-mclust@6.1.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://github.com/julieaubert/CHMM
Licenses: GPL 2
Build system: r
Synopsis: Coupled Hidden Markov Models
Description:

An exact and a variational inference for coupled Hidden Markov Models applied to the joint detection of copy number variations.

r-causaldt 1.0.0
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rpart@4.1.24 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r-utils@2.13.0 r-purrr@1.2.0 r-partykit@1.2-24 r-lifecycle@1.0.4 r-grf@2.5.0 r-ggplot2@4.0.1 r-ggparty@1.0.0.1 r-dplyr@1.1.4 r-bcf@2.0.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://tiffanymtang.github.io/causalDT/
Licenses: Expat
Build system: r
Synopsis: Causal Distillation Trees
Description:

Causal Distillation Tree (CDT) is a novel machine learning method for estimating interpretable subgroups with heterogeneous treatment effects. CDT allows researchers to fit any machine learning model (or metalearner) to estimate heterogeneous treatment effects for each individual, and then "distills" these predicted heterogeneous treatment effects into interpretable subgroups by fitting an ordinary decision tree to predict the previously-estimated heterogeneous treatment effects. This package provides tools to estimate causal distillation trees (CDT), as detailed in Huang, Tang, and Kenney (2025) <doi:10.48550/arXiv.2502.07275>.

r-commkern 1.0.1
Propagated dependencies: r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-matrix@1.7-4 r-gridextra@2.3 r-ggplot2@4.0.1 r-ggnewscale@0.5.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/aljensen89/CommKern
Licenses: GPL 2+
Build system: r
Synopsis: Network-Based Communities and Kernel Machine Methods
Description:

Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).

r-cancerr 0.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/giancarlodigi/cancerR
Licenses: GPL 2+
Build system: r
Synopsis: Classification of Cancer Using Administrative Data
Description:

Classifies the type of cancer using routinely collected data commonly found in cancer registries from pathology reports. The package implements the International Classification of Diseases for Oncology, 3rd Edition site (topography), histology (morphology), and behaviour codes of neoplasms to classify cancer type <https://www.who.int/standards/classifications/other-classifications/international-classification-of-diseases-for-oncology>. Classification in children utilize the International Classification of Childhood Cancer by Steliarova-Foucher et al. (2005) <doi:10.1002/cncr.20910>. Adolescent and young adult cancer classification is based on Barr et al. (2020) <doi:10.1002/cncr.33041>.

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