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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-homomorphicencryption 0.9.0
Propagated dependencies: r-polynom@1.4-1 r-hetools@1.0.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HomomorphicEncryption
Licenses: GPL 3+
Build system: r
Synopsis: BFV, BGV, CKKS Schema for Fully Homomorphic Encryption
Description:

This package implements the Brakerski-Fan-Vercauteren (BFV, 2012) <https://eprint.iacr.org/2012/144>, Brakerski-Gentry-Vaikuntanathan (BGV, 2014) <doi:10.1145/2633600>, and Cheon-Kim-Kim-Song (CKKS, 2016) <https://eprint.iacr.org/2016/421.pdf> schema for Fully Homomorphic Encryption. The included vignettes demonstrate the encryption procedures.

r-hdspatialscan 1.0.5
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HDSpatialScan
Licenses: GPL 3
Build system: r
Synopsis: Multivariate and Functional Spatial Scan Statistics
Description:

Allows to detect spatial clusters of abnormal values on multivariate or functional data (Frévent et al. (2022) <doi:10.32614/RJ-2022-045>). See also: Frévent et al. (2023) <doi:10.1093/jrsssc/qlad017>, Smida et al. (2022) <doi:10.1016/j.csda.2021.107378>, Frévent et al. (2021) <doi:10.1016/j.spasta.2021.100550>. Cucala et al. (2019) <doi:10.1016/j.spasta.2018.10.002>, Cucala et al. (2017) <doi:10.1016/j.spasta.2017.06.001>, Jung and Cho (2015) <doi:10.1186/s12942-015-0024-6>, Kulldorff et al. (2009) <doi:10.1186/1476-072X-8-58>.

r-highlightr 1.2.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://rachelesrogers.github.io/highlightr/
Licenses: Expat
Build system: r
Synopsis: Highlight Conserved Edits Across Versions of a Document
Description:

Input multiple versions of a source document, and receive HTML code for a highlighted version of the source document indicating the frequency of occurrence of phrases in the different versions. This method is described in Chapter 3 of Rogers (2024) <https://digitalcommons.unl.edu/dissertations/AAI31240449/>.

r-html2r 0.1.0
Propagated dependencies: r-shinythemes@1.2.0 r-shinyjqui@0.4.1 r-shinyace@0.4.4 r-shiny@1.11.1 r-glue@1.8.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/stla/html2R
Licenses: GPL 3
Build system: r
Synopsis: Convert 'HTML' to 'R' with a 'Shiny' App
Description:

This package provides a Shiny app allowing to convert HTML code to R code (e.g. <span>Hello</span> to tags$span("Hello")'), for usage in a Shiny UI.

r-hdar 1.0.7
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://www.wekeo.eu/
Licenses: GPL 3
Build system: r
Synopsis: 'REST' API Client for Accessing Data on 'WEkEO HDA V2'
Description:

This package provides seamless access to the WEkEO Harmonised Data Access (HDA) API, enabling users to query, download, and process data efficiently from the HDA platform. With hdar', researchers and data scientists can integrate the extensive HDA datasets into their R workflows, enhancing their data analysis capabilities. Comprehensive information on the API functionality and usage is available at <https://gateway.prod.wekeo2.eu/hda-broker/docs>.

r-h3lib 0.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/symbolixau/h3lib
Licenses: Expat
Build system: r
Synopsis: Exposes the 'Uber' 'H3' Library to R Packages
Description:

H3 is a hexagonal hierarchical spatial index developed by Uber <https://h3geo.org/>. This package exposes the source code of H3 (written in C') to routines that are callable through R'.

r-h2x2factorial 2.0.0
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=H2x2Factorial
Licenses: LGPL 2.1+
Build system: r
Synopsis: Sample Size Calculation in Hierarchical 2x2 Factorial Trials
Description:

This package implements the sample size methods for hierarchical 2x2 factorial trials under two choices of effect estimands and a series of hypothesis tests proposed in "Sample size calculation in hierarchical 2x2 factorial trials with unequal cluster sizes" (under review), and provides the table and plot generators for the sample size estimations.

r-hydroportailstats 1.1.0
Propagated dependencies: r-numderiv@2016.8-1.1 r-mvtnorm@1.3-3 r-evd@2.3-7.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/benRenard/HydroPortailStats
Licenses: GPL 3
Build system: r
Synopsis: 'HydroPortail' Statistical Functions
Description:

Statistical functions used in the French HydroPortail <https://hydro.eaufrance.fr/>. This includes functions to estimate distributions, quantile curves and uncertainties, along with various other utilities. Technical details are available (in French) in Renard (2016) <https://hal.inrae.fr/hal-02605318>.

r-hyperg 1.0.0
Propagated dependencies: r-rspectra@0.16-2 r-proxy@0.4-27 r-mclust@6.1.2 r-matrix@1.7-4 r-igraph@2.2.1 r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HyperG
Licenses: GPL 2+
Build system: r
Synopsis: Hypergraphs in R
Description:

This package implements various tools for storing and analyzing hypergraphs. Handles basic undirected, unweighted hypergraphs, and various ways of creating hypergraphs from a number of representations, and converting between graphs and hypergraphs.

r-hdbcp 1.0.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/JaeHoonKim98/hdbcp
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Change Point Detection for High-Dimensional Data
Description:

This package provides functions implementing change point detection methods using the maximum pairwise Bayes factor approach. Additionally, the package includes tools for generating simulated datasets for comparing and evaluating change point detection techniques.

r-httkexamples 0.0.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://chemicalinsights.ul.org/
Licenses: Expat
Build system: r
Synopsis: High-Throughput Toxicokinetics Examples
Description:

High throughput toxicokinetics ("HTTK") is the combination of 1) chemical-specific in vitro measurements or in silico predictions and 2) generic mathematical models, to predict absorption, distribution, metabolism, and excretion by the body. HTTK methods have been described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>) and Breen et al. (2021) (<doi:10.1080/17425255.2021.1935867>). Here we provide examples (vignettes) applying HTTK to solve various problems in bioinformatics, toxicology, and exposure science. In accordance with Davidson-Fritz et al. (2025) (<doi:10.1371/journal.pone.0321321>), whenever a new HTTK model is developed, the code to generate the figures evaluating that model is added as a new vignettte.

r-hashr 0.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/markvanderloo/hashr
Licenses: GPL 3
Build system: r
Synopsis: Hash R Objects to Integers Fast
Description:

Apply an adaptation of the SuperFastHash algorithm to any R object. Hash whole R objects or, for vectors or lists, hash R objects to obtain a set of hash values that is stored in a structure equivalent to the input. See <http://www.azillionmonkeys.com/qed/hash.html> for a description of the hash algorithm.

r-hdbinseg 1.0.3
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hdbinseg
Licenses: GPL 3+
Build system: r
Synopsis: Change-Point Analysis of High-Dimensional Time Series via Binary Segmentation
Description:

Binary segmentation methods for detecting and estimating multiple change-points in the mean or second-order structure of high-dimensional time series as described in Cho and Fryzlewicz (2014) <doi:10.1111/rssb.12079> and Cho (2016) <doi:10.1214/16-EJS1155>.

r-hdi 0.1-10
Propagated dependencies: r-scalreg@1.0.1 r-mass@7.3-65 r-linprog@0.9-4 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hdi
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: High-Dimensional Inference
Description:

Implementation of multiple approaches to perform inference in high-dimensional models.

r-hdcd 1.1
Propagated dependencies: r-rdpack@2.6.4 r-mclust@6.1.2
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HDCD
Licenses: GPL 3
Build system: r
Synopsis: High-Dimensional Changepoint Detection
Description:

Efficient implementations of the following multiple changepoint detection algorithms: Efficient Sparsity Adaptive Change-point estimator by Moen, Glad and Tveten (2023) <doi:10.48550/arXiv.2306.04702> , Informative Sparse Projection for Estimating Changepoints by Wang and Samworth (2017) <doi:10.1111/rssb.12243>, and the method of Pilliat et al (2023) <doi:10.1214/23-EJS2126>.

r-handcoder 0.1.2
Propagated dependencies: r-shinywidgets@0.9.0 r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/liserman/handcodeR/
Licenses: ASL 2.0
Build system: r
Synopsis: Text Annotation App
Description:

Shiny-App that allows to annotate vectors of texts to predefined categories by hand.

r-heatmapfit 2.0.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=heatmapFit
Licenses: GPL 2+
Build system: r
Synopsis: Fit Statistic for Binary Dependent Variable Models
Description:

Generates a fit plot for diagnosing misspecification in models of binary dependent variables, and calculates the related heatmap fit statistic described in Esarey and Pierce (2012) <DOI:10.1093/pan/mps026>.

r-hmclearn 0.0.5
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65 r-bayesplot@1.14.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hmclearn
Licenses: GPL 3
Build system: r
Synopsis: Fit Statistical Models Using Hamiltonian Monte Carlo
Description:

Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:. Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418, Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" <arXiv:1701.02434>, Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <arXiv:2006.16194>, Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955, Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034, Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174.

r-hbstm 1.0.2
Propagated dependencies: r-mass@7.3-65 r-maps@3.4.3 r-fbasics@4041.97
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HBSTM
Licenses: GPL 2+
Build system: r
Synopsis: Hierarchical Bayesian Space-Time Models for Gaussian Space-Time Data
Description:

Fits Hierarchical Bayesian space-Time models for Gaussian data. Furthermore, its functions have been implemented for analysing the fitting qualities of those models.

r-hsetest 0.1.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HSEtest
Licenses: GPL 3
Build system: r
Synopsis: Homogeneity of Stratum Effects Test
Description:

To test the homogeneity of stratum effects in stratified paired binary data.

r-hospitals 0.1.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/nhs-pt/hospitals
Licenses: CC0
Build system: r
Synopsis: Portuguese 'NHS' Hospitals
Description:

This package provides a data set of the Portuguese NHS hospitals.

r-hvt 26.1.2
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/Mu-Sigma/HVT
Licenses: ASL 2.0
Build system: r
Synopsis: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmaps for Data Analysis
Description:

Facilitates building topology preserving maps for data analysis.

r-hct 0.1.3
Propagated dependencies: r-rstan@2.32.7
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HCT
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Calculates Significance Criteria and Power for a Single Arm Trial
Description:

Given a database of previous treatment/placebo estimates, their standard errors and sample sizes, the program calculates a significance criteria and power estimate that takes into account the among trial variation.

r-htlr 1.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://longhaisk.github.io/HTLR/
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Logistic Regression with Heavy-Tailed Priors
Description:

Efficient Bayesian multinomial logistic regression based on heavy-tailed (hyper-LASSO, non-convex) priors. The posterior of coefficients and hyper-parameters is sampled with restricted Gibbs sampling for leveraging the high-dimensionality and Hamiltonian Monte Carlo for handling the high-correlation among coefficients. A detailed description of the method: Li and Yao (2018), Journal of Statistical Computation and Simulation, 88:14, 2827-2851, <doi:10.48550/arXiv.1405.3319>.

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Total results: 69112