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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-customizedtraining 1.3
Propagated dependencies: r-glmnet@4.1-10 r-fnn@1.1.4.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=customizedTraining
Licenses: GPL 2
Build system: r
Synopsis: Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models
Description:

Customized training is a simple technique for transductive learning, when the test covariates are known at the time of training. The method identifies a subset of the training set to serve as the training set for each of a few identified subsets in the training set. This package implements customized training for the glmnet() and cv.glmnet() functions.

r-cora 0.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/resteorts/cora
Licenses: CC0
Build system: r
Synopsis: Cora Data for Entity Resolution
Description:

Duplicated publication data (pre-processed and formatted) for entity resolution. This data set contains a total of 1879 records. The following variables are included in the data set: id, title, book title, authors, address, date, year, editor, journal, volume, pages, publisher, institution, type, tech, note. The data set has a respective gold data set that provides information on which records match based on id.

r-cenroc 2.0.0
Propagated dependencies: r-survival@3.8-3 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-icenreg@2.0.16 r-condsurv@2.0.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cenROC
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Time-Dependent ROC Curve and AUC for Censored Data
Description:

This package contains functions to estimate a smoothed and a non-smoothed (empirical) time-dependent receiver operating characteristic curve and the corresponding area under the receiver operating characteristic curve and the optimal cutoff point for the right and interval censored survival data. See Beyene and El Ghouch (2020)<doi:10.1002/sim.8671> and Beyene and El Ghouch (2022) <doi:10.1002/bimj.202000382>.

r-codalm 0.1.3
Propagated dependencies: r-squarem@2021.1 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/jfiksel/codalm
Licenses: GPL 2
Build system: r
Synopsis: Transformation-Free Linear Regression for Compositional Outcomes and Predictors
Description:

This package implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2022) <doi:10.1111/biom.13465> for transformation-free linear regression for compositional outcomes and predictors.

r-chemospecutils 1.0.5
Propagated dependencies: r-plotly@4.11.0 r-magrittr@2.0.4 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/bryanhanson/ChemoSpecUtils
Licenses: GPL 3
Build system: r
Synopsis: Functions Supporting Packages ChemoSpec and ChemoSpec2D
Description:

This package provides functions supporting the common needs of packages ChemoSpec and ChemoSpec2D'.

r-crwbmetareg 1.0
Propagated dependencies: r-sandwich@3.1-1 r-rfast2@0.1.5.6 r-lmtest@0.9-40
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=crwbmetareg
Licenses: GPL 2+
Build system: r
Synopsis: Cluster Robust Wild Bootstrap Meta Regression
Description:

In meta regression sometimes the studies have multiple effects that are correlated. For this reason cluster robust standard errors must be computed. However, since the clusters are unbalanced the wild bootstrap is suggested. See Oczkowski E. and Doucouliagos H. (2015). "Wine prices and quality ratings: a meta-regression analysis". American Journal of Agricultural Economics, 97(1): 103--121. <doi:10.1093/ajae/aau057> and Cameron A. C., Gelbach J. B. and Miller D. L. (2008). "Bootstrap-based improvements for inference with clustered errors". The Review of Economics and Statistics, 90(3): 414--427. <doi:10.1162/rest.90.3.414>.

r-circnntsraxial 0.1.0
Propagated dependencies: r-psychtools@2.5.7.22 r-circnntsr@2.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CircNNTSRaxial
Licenses: GPL 2+
Build system: r
Synopsis: Axial Data using NNTS Models
Description:

Statistical analysis of axial using distributions Nonnegative Trigonometric Sums (NNTS). The package includes functions for calculation of densities and distributions, for the estimation of parameters, and more. Fernandez-Duran, J.J. and Gregorio-Dominguez, M.M. (2025), Multimodal distributions for circular axial data", <doi:10.48550/arXiv.2504.04681>.

r-cpm 2.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cpm
Licenses: GPL 3
Build system: r
Synopsis: Sequential and Batch Change Detection Using Parametric and Nonparametric Methods
Description:

Sequential and batch change detection for univariate data streams, using the change point model framework. Functions are provided to allow nonparametric distribution-free change detection in the mean, variance, or general distribution of a given sequence of observations. Parametric change detection methods are also provided for Gaussian, Bernoulli and Exponential sequences. Both the batch (Phase I) and sequential (Phase II) settings are supported, and the sequences may contain either a single or multiple change points. A full description of this package is available in Ross, G.J (2015) - "Parametric and nonparametric sequential change detection in R" available at <https://www.jstatsoft.org/article/view/v066i03>.

r-corrtable 0.1.1
Propagated dependencies: r-hmisc@5.2-4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=corrtable
Licenses: GPL 3
Build system: r
Synopsis: Creates and Saves Out a Correlation Table with Significance Levels Indicated
Description:

After using this, a publication-ready correlation table with p-values indicated will be created. The input can be a full data frame; any string and Boolean terms will be dropped as part of functionality. Correlations and p-values are calculated using the Hmisc framework. Output of the correlation_matrix() function is a table of strings; this gets saved out to a .csv2 with the save_correlation_matrix() function for easy insertion into a paper. For more details about the process, consult <https://paulvanderlaken.com/2020/07/28/publication-ready-correlation-matrix-significance-r/>.

r-certara-rsnlme-modelbuilder 3.0.1
Propagated dependencies: r-shinywidgets@0.9.0 r-shinymeta@0.2.1 r-shinyjs@2.1.0 r-shinyace@0.4.4 r-shiny@1.11.1 r-magrittr@2.0.4 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-fs@1.6.6 r-dt@0.34.0 r-data-table@1.17.8 r-certara-rsnlme@3.1.0.1 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://certara.github.io/R-RsNLME-model-builder/
Licenses: LGPL 3
Build system: r
Synopsis: Pharmacometric Model Building Using 'shiny'
Description:

Develop Nonlinear Mixed Effects (NLME) models for pharmacometrics using a shiny interface. The Pharmacometric Modeling Language (PML) code updates in real time given changes to user inputs. Models can be executed using the Certara.RsNLME package. Additional support to generate the underlying Certara.RsNLME code to recreate the corresponding model in R is provided in the user interface.

r-contdid 0.1.0
Propagated dependencies: r-splines2@0.5.4 r-sandwich@3.1-1 r-ptetools@1.0.0 r-npiv@0.1.3 r-mass@7.3-65 r-ggplot2@4.0.1 r-checkmate@2.3.3 r-bmisc@1.4.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://bcallaway11.github.io/contdid/
Licenses: GPL 3
Build system: r
Synopsis: Difference-in-Differences with a Continuous Treatment
Description:

This package provides methods for difference-in-differences with a continuous treatment and staggered treatment adoption. Includes estimation of treatment effects and causal responses as a function of the dose, event studies indexed by length of exposure to the treatment, and aggregation into overall average effects. Uniform inference procedures are included, along with both parametric and nonparametric models for treatment effects. The methods are based on Callaway, Goodman-Bacon, and Sant'Anna (2025) <doi:10.48550/arXiv.2107.02637>.

r-coroica 1.0.2
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/sweichwald/coroICA-R
Licenses: AGPL 3
Build system: r
Synopsis: Confounding Robust Independent Component Analysis for Noisy and Grouped Data
Description:

This package contains an implementation of a confounding robust independent component analysis (ICA) for noisy and grouped data. The main function coroICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding based on user-specified groups. Additionally, the package contains the function uwedge() which can be used to approximately jointly diagonalize a list of matrices. For more details see the project website <https://sweichwald.de/coroICA/>.

r-cleancall 0.1.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/r-lib/cleancall#readme
Licenses: Expat
Build system: r
Synopsis: C Resource Cleanup via Exit Handlers
Description:

Wrapper of .Call() that runs exit handlers to clean up C resources. Helps managing C (non-R) resources while using the R API.

r-coordinatecleaner 3.0.1
Dependencies: gdal@3.8.2
Propagated dependencies: r-tidyselect@1.2.1 r-terra@1.8-86 r-rnaturalearth@1.1.0 r-rgbif@3.8.4 r-ggplot2@4.0.1 r-geosphere@1.5-20 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://ropensci.github.io/CoordinateCleaner/
Licenses: GPL 3
Build system: r
Synopsis: Automated Cleaning of Occurrence Records from Biological Collections
Description:

Automated flagging of common spatial and temporal errors in biological and paleontological collection data, for the use in conservation, ecology and paleontology. Includes automated tests to easily flag (and exclude) records assigned to country or province centroid, the open ocean, the headquarters of the Global Biodiversity Information Facility, urban areas or the location of biodiversity institutions (museums, zoos, botanical gardens, universities). Furthermore identifies per species outlier coordinates, zero coordinates, identical latitude/longitude and invalid coordinates. Also implements an algorithm to identify data sets with a significant proportion of rounded coordinates. Especially suited for large data sets. The reference for the methodology is: Zizka et al. (2019) <doi:10.1111/2041-210X.13152>.

r-crtconjoint 0.1.0
Propagated dependencies: r-snow@0.4-4 r-rcpp@1.1.0 r-foreach@1.5.2 r-dosnow@1.0.20
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/daewoongham97/CRTConjoint
Licenses: GPL 3+
Build system: r
Synopsis: Conditional Randomization Testing (CRT) Approach for Conjoint Analysis
Description:

Computes p-value according to the CRT using the HierNet test statistic. For more details, see Ham, Imai, Janson (2022) "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" <arXiv:2201.08343>.

r-coat 0.2.2
Propagated dependencies: r-partykit@1.2-24
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=coat
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Conditional Method Agreement Trees (COAT)
Description:

Agreement of continuously scaled measurements made by two techniques, devices or methods is usually evaluated by the well-established Bland-Altman analysis or plot. Conditional method agreement trees (COAT), proposed by Karapetyan, Zeileis, Henriksen, and Hapfelmeier (2025) <doi:10.1093/jrsssc/qlae077>, embed the Bland-Altman analysis in the framework of recursive partitioning to explore heterogeneous method agreement in dependence of covariates. COAT can also be used to perform a Bland-Altman test for differences in method agreement.

r-ctf 0.1.0
Propagated dependencies: r-jsonlite@2.0.0 r-iotools@0.3-5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/julianofhernandez/ctf
Licenses: Expat
Build system: r
Synopsis: Read and Write Column Text Format (CTF)
Description:

Column Text Format (CTF) is a new tabular data format designed for simplicity and performance. CTF is the simplest column store you can imagine: plain text files for each column in a table, and a metadata file. The underlying plain text means the data is human readable and familiar to programmers, unlike specialized binary formats. CTF is faster than row oriented formats like CSV when loading a subset of the columns in a table. This package provides functions to read and write CTF data from R.

r-cif 0.1.1
Propagated dependencies: r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cif
Licenses: GPL 3
Build system: r
Synopsis: Cointegrated ICU Forecasting
Description:

Set of forecasting tools to predict ICU beds using a Vector Error Correction model with a single cointegrating vector. Method described in Berta, P. Lovaglio, P.G. Paruolo, P. Verzillo, S., 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand" Health, Econometrics and Data Group (HEDG) Working Papers 20/16, HEDG, Department of Economics, University of York, <https://www.york.ac.uk/media/economics/documents/hedg/workingpapers/2020/2016.pdf>.

r-clickstream 1.3.4
Propagated dependencies: r-rsolnp@2.0.1 r-reshape2@1.4.5 r-plyr@1.8.9 r-mass@7.3-65 r-linprog@0.9-4 r-igraph@2.2.1 r-ggplot2@4.0.1 r-data-table@1.17.8 r-clickclust@1.1.6 r-arules@1.7-11
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clickstream
Licenses: GPL 2
Build system: r
Synopsis: Analyzes Clickstreams Based on Markov Chains
Description:

This package provides a set of tools to read, analyze and write lists of click sequences on websites (i.e., clickstream). A click can be represented by a number, character or string. Clickstreams can be modeled as zero- (only computes occurrence probabilities), first- or higher-order Markov chains.

r-cookiecutter 0.1.0
Propagated dependencies: r-whisker@0.4.1 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-mime@0.13 r-jsonlite@2.0.0 r-fs@1.6.6
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/felixhenninger/cookiecutter/
Licenses: FSDG-compatible
Build system: r
Synopsis: Generate Project Files from a Template
Description:

Generate project files and directories following a pre-made template. You can specify variables to customize file names and content, and flexibly adapt the template to your needs. cookiecutter for R implements a subset of the excellent cookiecutter package for the Python programming language (<https://github.com/cookiecutter/>), and aims to be largely compatible with the original cookiecutter template format.

r-crank 1.1-2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=crank
Licenses: GPL 2+
Build system: r
Synopsis: Completing Ranks
Description:

This package provides functions for completing and recalculating rankings and sorting.

r-cor 0.2.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=COR
Licenses: Expat
Build system: r
Synopsis: The COR for Optimal Subset Selection in Distributed Estimation
Description:

An algorithm of optimal subset selection, related to Covariance matrices, observation matrices and Response vectors (COR) to select the optimal subsets in distributed estimation. The philosophy of the package is described in Guo G. (2024) <doi:10.1007/s11222-024-10471-z>.

r-cohortgenerator 1.1.0
Propagated dependencies: r-tibble@3.3.0 r-stringi@1.8.7 r-sqlrender@1.19.4 r-rlang@1.1.6 r-resultmodelmanager@0.6.2 r-readr@2.1.6 r-r6@2.6.1 r-parallellogger@3.5.1 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-dplyr@1.1.4 r-digest@0.6.39 r-databaseconnector@7.1.0 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://ohdsi.github.io/CohortGenerator/
Licenses: FSDG-compatible
Build system: r
Synopsis: Cohort Generation for the OMOP Common Data Model
Description:

Generate cohorts and subsets using an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. Cohorts are defined using CIRCE (<https://github.com/ohdsi/circe-be>) or SQL compatible with SqlRender (<https://github.com/OHDSI/SqlRender>).

r-csdata 2024.4.26
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/csdata/
Licenses: Expat
Build system: r
Synopsis: Structural Data for Norway
Description:

Datasets relating to population in municipalities, municipality/county matching, and how different municipalities have merged/redistricted over time from 2006 to 2024.

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