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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-colourvalues 0.3.11
Propagated dependencies: r-rcpp@1.1.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://symbolixau.github.io/colourvalues/
Licenses: GPL 3
Build system: r
Synopsis: Assigns Colours to Values
Description:

Maps one of the viridis colour palettes, or a user-specified palette to values. Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith, and were set as the default palette for the Python Matplotlib library <https://matplotlib.org/>. Other palettes available in this library have been derived from RColorBrewer <https://CRAN.R-project.org/package=RColorBrewer> and colorspace <https://CRAN.R-project.org/package=colorspace> packages.

r-compositionalhdda 1.0
Propagated dependencies: r-rfast@2.1.5.2 r-hdclassif@2.2.2 r-compositional@8.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CompositionalHDDA
Licenses: GPL 2+
Build system: r
Synopsis: High Dimensional Discriminant Analysis with Compositional Data
Description:

High dimensional discriminant analysis with compositional data is performed. The compositional data are first transformed using the alpha-transformation of Tsagris M., Preston S. and Wood A.T.A. (2011) <doi:10.48550/arXiv.1106.1451>, and then the High Dimensional Discriminant Analysis (HDDA) algorithm of Bouveyron C. Girard S. and Schmid C. (2007) <doi:10.1080/03610920701271095> is applied.

r-cmhsu 0.0.6.9
Propagated dependencies: r-tidyr@1.3.1 r-purrr@1.2.0 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://cran.r-project.org/package=CMHSU
Licenses: GPL 3
Build system: r
Synopsis: Mental Health Status, Substance Use Status and their Concurrent Status in North American Healthcare Administrative Databases
Description:

Patients Mental Health (MH) status, Substance Use (SU) status, and concurrent MH/SU status in the American/Canadian Healthcare Administrative Databases can be identified. The detection is based on given parameters of interest by clinicians including the list of plausible ICD MH/SU codes (3/4/5 characters), the required number of visits of hospital for MH/SU , the required number of visits of service physicians for MH/SU, and the maximum time span within MH visits, within SU visits, and, between MH and SU visits. Methods are described in: Khan S <https://pubmed.ncbi.nlm.nih.gov/29044442/>, Keen C, et al. (2021) <doi:10.1111/add.15580>, Lavergne MR, et al. (2022) <doi:10.1186/s12913-022-07759-z>, Casillas, S M, et al. (2022) <doi:10.1016/j.abrep.2022.100464>, CIHI (2022) <https://www.cihi.ca/en>, CDC (2024) <https://www.cdc.gov>, WHO (2019) <https://icd.who.int/en>.

r-complex 1.0.2
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-nloptr@2.2.1 r-mvtnorm@1.3-3 r-legion@0.2.1 r-greybox@2.0.7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/config-i1/complex
Licenses: LGPL 2.1
Build system: r
Synopsis: Time Series Analysis and Forecasting Using Complex Variables
Description:

This package implements the instruments for complex-valued modelling, including time series analysis and forecasting. This is based on the monograph by Svetunkov & Svetunkov (2024) <doi: 10.1007/978-3-031-62608-1>.

r-clintrialx 0.1.1
Propagated dependencies: r-tibble@3.3.0 r-rpostgresql@0.7-8 r-rmarkdown@2.30 r-readr@2.1.6 r-progress@1.2.3 r-lubridate@1.9.4 r-httr@1.4.7 r-dplyr@1.1.4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://www.indraneelchakraborty.com/clintrialx/
Licenses: ASL 2.0
Build system: r
Synopsis: Connect and Work with Clinical Trials Data Sources
Description:

Are you spending too much time fetching and managing clinical trial data? Struggling with complex queries and bulk data extraction? What if you could simplify this process with just a few lines of code? Introducing clintrialx - Fetch clinical trial data from sources like ClinicalTrials.gov <https://clinicaltrials.gov/> and the Clinical Trials Transformation Initiative - Access to Aggregate Content of ClinicalTrials.gov database <https://aact.ctti-clinicaltrials.org/>, supporting pagination and bulk downloads. Also, you can generate HTML reports based on the data obtained from the sources!

r-ciphertext 0.1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/Luigi-Annic/ciphertext
Licenses: GPL 3
Build system: r
Synopsis: Classical Cryptography Methods for Words and Phrases
Description:

Classical cryptography methods for words and brief phrases. Substitution, transposition and concealment (null) ciphers are available, like Caesar, Vigenère, Atbash, affine, simple substitution, Playfair, rail fence, Scytale, single column, bifid, trifid, and Polybius ciphers.

r-clustlearn 1.0.0
Propagated dependencies: r-proxy@0.4-27 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/Ediu3095/clustlearn
Licenses: Expat
Build system: r
Synopsis: Learn Clustering Techniques Through Examples and Code
Description:

Clustering methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in Ezugwu et. al., (2022) <doi:10.1016/j.engappai.2022.104743>; and datasets to test them on, which highlight the strengths and weaknesses of each technique, as presented in the clustering section of scikit-learn (Pedregosa et al., 2011) <https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html>.

r-cmf 1.0.3
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=CMF
Licenses: GPL 2+
Build system: r
Synopsis: Collective Matrix Factorization
Description:

Collective matrix factorization (CMF) finds joint low-rank representations for a collection of matrices with shared row or column entities. This code learns a variational Bayesian approximation for CMF, supporting multiple likelihood potentials and missing data, while identifying both factors shared by multiple matrices and factors private for each matrix. For further details on the method see Klami et al. (2014) <arXiv:1312.5921>. The package can also be used to learn Bayesian canonical correlation analysis (CCA) and group factor analysis (GFA) models, both of which are special cases of CMF. This is likely to be useful for people looking for CCA and GFA solutions supporting missing data and non-Gaussian likelihoods. See Klami et al. (2013) <https://research.cs.aalto.fi/pml/online-papers/klami13a.pdf> and Virtanen et al. (2012) <http://proceedings.mlr.press/v22/virtanen12.html> for details on Bayesian CCA and GFA, respectively.

r-climarep 1.0
Propagated dependencies: r-tidyterra@1.0.0 r-terra@1.8-86 r-sf@1.0-23 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=ClimaRep
Licenses: Expat
Build system: r
Synopsis: Estimating Climate Representativeness
Description:

Offers tools to estimate the climate representativeness of reference polygons and quantifies its transformation under future climate change scenarios. Approaches described in Mingarro and Lobo (2018) <doi:10.32800/abc.2018.41.0333> and Mingarro and Lobo (2022) <doi:10.1017/S037689292100014X>.

r-clustcurv 3.0.1
Propagated dependencies: r-survminer@0.5.1 r-survival@3.8-3 r-rcolorbrewer@1.1-3 r-npregfast@1.6.0 r-gmedian@1.2.7 r-ggplot2@4.0.1 r-ggfortify@0.4.19 r-foreach@1.5.2 r-dorng@1.8.6.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/noramvillanueva/clustcurv
Licenses: Expat
Build system: r
Synopsis: Determining Groups in Multiples Curves
Description:

This package provides a method for determining groups in multiple curves with an automatic selection of their number based on k-means or k-medians algorithms. The selection of the optimal number is provided by bootstrap methods or other approaches with lower computational cost. The methodology can be applied both in regression and survival framework. Implemented methods are: Grouping multiple survival curves described by Villanueva et al. (2018) <doi:10.1002/sim.8016>.

r-czso 0.4.4
Propagated dependencies: r-tibble@3.3.0 r-stringi@1.8.7 r-rlang@1.1.6 r-readr@2.1.6 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 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://github.com/petrbouchal/czso
Licenses: Expat
Build system: r
Synopsis: Use Open Data from the Czech Statistical Office in R
Description:

Get programmatic access to the open data provided by the Czech Statistical Office (CZSO, <https://csu.gov.cz>).

r-confsam 0.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=confSAM
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Estimates and Bounds for the False Discovery Proportion, by Permutation
Description:

For multiple testing. Computes estimates and confidence bounds for the False Discovery Proportion (FDP), the fraction of false positives among all rejected hypotheses. The methods in the package use permutations of the data. Doing so, they take into account the dependence structure in the data.

r-channelattribution 2.2.4
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://channelattribution.io
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Markov Model for Online Multi-Channel Attribution
Description:

Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.

r-chilemapas 0.4.0
Propagated dependencies: r-stringr@1.6.0 r-sf@1.0-23 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://pacha.dev/chilemapas/
Licenses: GPL 3
Build system: r
Synopsis: Mapas de las Divisiones Politicas y Administrativas de Chile (Maps of the Political and Administrative Divisions of Chile)
Description:

Mapas terrestres con topologias simplificadas. Estos mapas no tienen precision geodesica, por lo que aplica el DFL-83 de 1979 de la Republica de Chile y se consideran referenciales sin validez legal. No se incluyen los territorios antarticos y bajo ningun evento estos mapas significan que exista una cesion u ocupacion de territorios soberanos en contra del Derecho Internacional por parte de Chile. Esta paquete esta documentado intencionalmente en castellano asciificado para que funcione sin problema en diferentes plataformas. (Terrestrial maps with simplified toplogies. These maps lack geodesic precision, therefore DFL-83 1979 of the Republic of Chile applies and are considered to have no legal validity. Antartic territories are excluded and under no event these maps mean there is a cession or occupation of sovereign territories against International Laws from Chile. This package was intentionally documented in asciified spanish to make it work without problem on different platforms.).

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-catcont 0.5.0
Propagated dependencies: 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=catcont
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Test, Identify, Select and Mutate Categorical or Continuous Values
Description:

This package provides methods and utilities for testing, identifying, selecting and mutating objects as categorical or continous types. These functions work on both atomic vectors as well as recursive objects: data.frames, data.tables, tibbles, lists, etc..

r-cocorresp 0.4-6
Propagated dependencies: r-vegan@2.7-2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://gavinsimpson.github.io/cocorresp/
Licenses: GPL 2
Build system: r
Synopsis: Co-Correspondence Analysis Methods
Description:

Fits predictive and symmetric co-correspondence analysis (CoCA) models to relate one data matrix to another data matrix. More specifically, CoCA maximises the weighted covariance between the weighted averaged species scores of one community and the weighted averaged species scores of another community. CoCA attempts to find patterns that are common to both communities.

r-chatai4r 1.3.1
Propagated dependencies: r-rstudioapi@0.17.1 r-jsonlite@2.0.0 r-igraph@2.2.1 r-httr@1.4.7 r-glue@1.8.0 r-future@1.68.0 r-deeprstudio@0.0.9 r-curl@7.0.0 r-crayon@1.5.3 r-clipr@0.8.0 r-base64enc@0.1-3 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://kumes.github.io/chatAI4R/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Chat-Based Interactive Artificial Intelligence for R
Description:

The Large Language Model (LLM) represents a groundbreaking advancement in data science and programming, and also allows us to extend the world of R. A seamless interface for integrating the OpenAI Web APIs into R is provided in this package. This package leverages LLM-based AI techniques, enabling efficient knowledge discovery and data analysis. The previous functions such as seamless translation and image generation have been moved to other packages deepRstudio and stableDiffusion4R'.

r-constrainedkriging 0.2-11
Propagated dependencies: r-spatialcovariance@0.6-9 r-sp@2.2-0 r-sf@1.0-23
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=constrainedKriging
Licenses: GPL 2+
Build system: r
Synopsis: Constrained, Covariance-Matching Constrained and Universal Point or Block Kriging
Description:

This package provides functions for efficient computation of non-linear spatial predictions with local change of support (Hofer, C. and Papritz, A. (2011) "constrainedKriging: An R-package for customary, constrained and covariance-matching constrained point or block kriging" <doi:10.1016/j.cageo.2011.02.009>). This package supplies functions for two-dimensional spatial interpolation by constrained (Cressie, N. (1993) "Aggregation in geostatistical problems" <doi:10.1007/978-94-011-1739-5_3>), covariance-matching constrained (Aldworth, J. and Cressie, N. (2003) "Prediction of nonlinear spatial functionals" <doi:10.1016/S0378-3758(02)00321-X>) and universal (external drift) Kriging for points or blocks of any shape from data with a non-stationary mean function and an isotropic weakly stationary covariance function. The linear spatial interpolation methods, constrained and covariance-matching constrained Kriging, provide approximately unbiased prediction for non-linear target values under change of support. This package extends the range of tools for spatial predictions available in R and provides an alternative to conditional simulation for non-linear spatial prediction problems with local change of support.

r-comics 1.0.4
Propagated dependencies: r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://dcq.tau.ac.il/
Licenses: GPL 2
Build system: r
Synopsis: Computational Methods for Immune Cell-Type Subsets
Description:

Provided are Computational methods for Immune Cell-type Subsets, including:(1) DCQ (Digital Cell Quantifier) to infer global dynamic changes in immune cell quantities within a complex tissue; and (2) VoCAL (Variation of Cell-type Abundance Loci) a deconvolution-based method that utilizes transcriptome data to infer the quantities of immune-cell types, and then uses these quantitative traits to uncover the underlying DNA loci.

r-cmgnd 0.1.1
Propagated dependencies: r-rcppalgos@2.9.3 r-purrr@1.2.0 r-lubridate@1.9.4 r-gnorm@1.0.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/pierdutt/cmgnd
Licenses: GPL 3+
Build system: r
Synopsis: Constrained Mixture of Generalized Normal Distributions
Description:

The cmgnd implements the constrained mixture of generalized normal distributions model, a flexible statistical framework for modelling univariate data exhibiting non-normal features such as skewness, multi-modality, and heavy tails. By imposing constraints on model parameters, the cmgnd reduces estimation complexity while maintaining high descriptive power, offering an efficient solution in the presence of distributional irregularities. For more details see Duttilo and Gattone (2025) <doi:10.1007/s00180-025-01638-x> and Duttilo et al (2025) <doi:10.48550/arXiv.2506.03285>.

r-conjurer 1.7.1
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.foyi.co.nz/posts/documentation/documentationconjurer/
Licenses: Expat
Build system: r
Synopsis: Parametric Method for Generating Synthetic Data
Description:

Generates synthetic data distributions to enable testing various modelling techniques in ways that real data does not allow. Noise can be added in a controlled manner such that the data seems real. This methodology is generic and therefore benefits both the academic and industrial research.

r-cosmos 2.1.2
Propagated dependencies: r-pracma@2.4.6 r-plot3d@1.4.2 r-nloptr@2.2.1 r-mvtnorm@1.3-3 r-mba@0.1-2 r-matrixcalc@1.0-6 r-matrix@1.7-4 r-mar@1.2-0 r-ggquiver@0.4.0 r-ggplot2@4.0.1 r-directlabels@2025.6.24 r-data-table@1.17.8 r-cowplot@1.2.0 r-animation@2.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/TycheLab/CoSMoS
Licenses: AGPL 3
Build system: r
Synopsis: Complete Stochastic Modelling Solution
Description:

Makes univariate, multivariate, or random fields simulations precise and simple. Just select the desired time series or random fieldsâ properties and it will do the rest. CoSMoS is based on the framework described in Papalexiou (2018, <doi:10.1016/j.advwatres.2018.02.013>), extended for random fields in Papalexiou and Serinaldi (2020, <doi:10.1029/2019WR026331>), and further advanced in Papalexiou et al. (2021, <doi:10.1029/2020WR029466>) to allow fine-scale space-time simulation of storms (or even cyclone-mimicking fields).

r-cpsurv 1.0.0
Propagated dependencies: r-survival@3.8-3 r-muhaz@1.2.6.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CPsurv
Licenses: GPL 2
Build system: r
Synopsis: Nonparametric Change Point Estimation for Survival Data
Description:

Nonparametric change point estimation for survival data based on p-values of exact binomial tests.

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