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      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
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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-hivdata 0.1.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hivdata
Licenses: GPL 2+
Build system: r
Synopsis: Six-Year Chronological Data of HIV and ART Cases in Pakistan
Description:

We provide the monthly number of HIV and antiretroviral therapy (ART) cases of male, female, children and transgender as well as for the whole of Pakistan reported at various treatment centers in Pakistan from January 2016 to December 2021. Related works include: a) Imran, M., Nasir, J. A., & Riaz, S. (2018). Regional pattern of HIV cases in Pakistan. Journal of Postgraduate Medical Institute, 32(1), 9-13. <https://jpmi.org.pk/index.php/jpmi/article/view/2108>.

r-hdsvm 1.0.2
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hdsvm
Licenses: GPL 2
Build system: r
Synopsis: Fast Algorithm for Support Vector Machine
Description:

This package implements an efficient algorithm for fitting the entire regularization path of support vector machine models with elastic-net penalties using a generalized coordinate descent scheme. The framework also supports SCAD and MCP penalties. It is designed for high-dimensional datasets and emphasizes numerical accuracy and computational efficiency. This package implements the algorithms proposed in Tang, Q., Zhang, Y., & Wang, B. (2022) <https://openreview.net/pdf?id=RvwMTDYTOb>.

r-harrypotter 2.1.1
Propagated dependencies: r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/aljrico/harrypotter
Licenses: Expat
Build system: r
Synopsis: Palettes Generated from All "Harry Potter" Movies
Description:

Implementation of characteristic palettes inspired in the Wizarding World and the Harry Potter movie franchise.

r-hyper2 3.2
Propagated dependencies: r-rdpack@2.6.4 r-rcpp@1.1.0 r-partitions@1.10-9 r-magrittr@2.0.4 r-disordr@0.9-8-5 r-cubature@2.1.4-1 r-calibrator@1.2-8 r-alabama@2023.1.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/RobinHankin/hyper2
Licenses: GPL 2+
Build system: r
Synopsis: The Hyperdirichlet Distribution, Mark 2
Description:

This package provides a suite of routines for the hyperdirichlet distribution and reified Bradley-Terry; supersedes the hyperdirichlet package; uses disordR discipline <doi:10.48550/ARXIV.2210.03856>. To cite in publications please use Hankin 2017 <doi:10.32614/rj-2017-061>, and for Generalized Plackett-Luce likelihoods use Hankin 2024 <doi:10.18637/jss.v109.i08>.

r-hzip 0.1.1
Propagated dependencies: r-vgam@1.1-13 r-tibble@3.3.0 r-statmod@1.5.1 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pscl@1.5.9 r-ggplot2@4.0.1 r-formula@1.2-5 r-dplyr@1.1.4 r-cubature@2.1.4-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/carrascojalmar/HZIP
Licenses: GPL 3
Build system: r
Synopsis: Likelihood-Based Inference for Joint Modeling of Correlated Count and Binary Outcomes with Extra Variability and Zeros
Description:

Inference approach for jointly modeling correlated count and binary outcomes. This formulation allows simultaneous modeling of zero inflation via the Bernoulli component while providing a more accurate assessment of the Hierarchical Zero-Inflated Poisson's parsimony (Lizandra C. Fabio, Jalmar M. F. Carrasco, Victor H. Lachos and Ming-Hui Chen, Likelihood-based inference for joint modeling of correlated count and binary outcomes with extra variability and zeros, 2025, under submission).

r-hrw 1.0-6
Propagated dependencies: r-kernsmooth@2.23-26
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HRW
Licenses: GPL 2+
Build system: r
Synopsis: Datasets, Functions and Scripts for Semiparametric Regression Supporting Harezlak, Ruppert & Wand (2018)
Description:

The book "Semiparametric Regression with R" by J. Harezlak, D. Ruppert & M.P. Wand (2018, Springer; ISBN: 978-1-4939-8851-8) makes use of datasets and scripts to explain semiparametric regression concepts. Each of the book's scripts are contained in this package as well as datasets that are not within other R packages. Functions that aid semiparametric regression analysis are also included.

r-histoslider 0.1.1
Propagated dependencies: r-shiny@1.11.1 r-rlang@1.1.6 r-reactr@0.6.1 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=histoslider
Licenses: Expat
Build system: r
Synopsis: Histogram Slider Input for 'Shiny'
Description:

This package provides a histogram slider input binding for use in Shiny'. Currently supports creating histograms from numeric, date, and date-time vectors.

r-hcd 1.0
Propagated dependencies: r-stringr@1.6.0 r-rspectra@0.16-2 r-randnet@1.0 r-matrix@1.7-4 r-irlba@2.3.5.1 r-dendextend@1.19.1 r-data-tree@1.2.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HCD
Licenses: GPL 2+
Build system: r
Synopsis: Hierarchical Community Detection by Recursive Partitioning
Description:

Hierarchical community detection on networks by a recursive spectral partitioning strategy, which is shown to be effective and efficient in Li, Lei, Bhattacharyya, Sarkar, Bickel, and Levina (2018) <arXiv:1810.01509>. The package also includes a data generating function for a binary tree stochastic block model, a special case of stochastic block model that admits hierarchy between communities.

r-h2otools 0.4
Propagated dependencies: r-h2o@3.44.0.3 r-curl@7.0.0 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/haghish/h2otools
Licenses: Expat
Build system: r
Synopsis: Machine Learning Model Evaluation for 'h2o' Package
Description:

Enhances the H2O platform by providing tools for detailed evaluation of machine learning models. It includes functions for bootstrapped performance evaluation, extended F-score calculations, and various other metrics, aimed at improving model assessment.

r-hdsinrdata 0.3.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HDSinRdata
Licenses: FSDG-compatible
Build system: r
Synopsis: Data for the 'Mastering Health Data Science Using R' Online Textbook
Description:

This package contains ten datasets used in the chapters and exercises of Paul, Alice (2023) "Health Data Science in R" <https://alicepaul.github.io/health-data-science-using-r/>.

r-healthyr-ai 0.1.1
Propagated dependencies: r-yardstick@1.3.2 r-workflows@1.3.0 r-tune@2.0.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-recipes@1.3.1 r-purrr@1.2.0 r-parsnip@1.3.3 r-modeltime@1.3.5 r-magrittr@2.0.4 r-h2o@3.44.0.3 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-dials@1.4.2 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://www.spsanderson.com/healthyR.ai/
Licenses: Expat
Build system: r
Synopsis: The Machine Learning and AI Modeling Companion to 'healthyR'
Description:

Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include predicting length of stay, and readmits. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.

r-happign 0.3.7
Propagated dependencies: r-xml2@1.5.0 r-terra@1.8-86 r-sf@1.0-23 r-jsonlite@2.0.0 r-httr2@1.2.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/paul-carteron
Licenses: GPL 3+
Build system: r
Synopsis: R Interface to 'IGN' Web Services
Description:

Automatic open data acquisition from resources of IGN ('Institut National de Information Geographique et forestiere') (<https://www.ign.fr/>). Available datasets include various types of raster and vector data, such as digital elevation models, state borders, spatial databases, cadastral parcels, and more. happign also provide access to API Carto (<https://apicarto.ign.fr/api/doc/>).

r-helpersmg 2025.12.22
Propagated dependencies: r-rlang@1.1.6 r-matrix@1.7-4 r-mass@7.3-65 r-ggplot2@4.0.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HelpersMG
Licenses: GPL 2
Build system: r
Synopsis: Tools for Various R Functions Helpers
Description:

This package contains miscellaneous functions useful for managing NetCDF files (see <https://en.wikipedia.org/wiki/NetCDF>), get moon phase and time for sun rise and fall, tide level, analyse and reconstruct periodic time series of temperature with irregular sinusoidal pattern, show scales and wind rose in plot with change of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot graphs or boxplot with error bars, search files in disk by there names or their content, read the contents of all files from a folder at one time.

r-heiscore 0.1.4
Propagated dependencies: r-viridis@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinythemes@1.2.0 r-shiny@1.11.1 r-rlang@1.1.6 r-magrittr@2.0.4 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-fmsb@0.7.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/abhrastat/heiscore
Licenses: Expat
Build system: r
Synopsis: Score and Plot the Healthy Eating Index from NHANES Data
Description:

Calculate and visualize Healthy Eating Index (HEI) scores from National Health and Nutrition Examination Survey 24-hour dietary recall data utilizing three methods recommended by the National Cancer Institute (2024) <https://epi.grants.cancer.gov/hei/hei-methods-and-calculations.html#:~:text=To%20use%20the%20simple%20HEI,the%20total%20scores%20across%20individuals.>. Effortlessly analyze HEI scores across different demographic groups and years.

r-healthyaddress 0.5.1
Propagated dependencies: r-qs2@0.1.6 r-magrittr@2.0.4 r-hutilscpp@0.10.10 r-hutils@2.0.0 r-fst@0.9.8 r-fastmatch@1.1-6 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/HughParsonage/healthyAddress
Licenses: GPL 2
Build system: r
Synopsis: Convert Addresses to Standard Inputs
Description:

Efficient tools for parsing and standardizing Australian addresses from textual data. It utilizes optimized algorithms to accurately identify and extract components of addresses, such as street names, types, and postcodes, especially for large batched data in contexts where sending addresses to internet services may be slow or inappropriate. The core functionality is built on fast string processing techniques to handle variations in address formats and abbreviations commonly found in Australian address data. Designed for data scientists, urban planners, and logistics analysts, the package facilitates the cleaning and normalization of address information, supporting better data integration and analysis in urban studies, geography, and related fields.

r-hiclimr 2.2.1
Dependencies: netcdf@4.9.0
Propagated dependencies: r-ncdf4@1.24
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://hsbadr.github.io/HiClimR/
Licenses: GPL 3
Build system: r
Synopsis: Hierarchical Climate Regionalization
Description:

This package provides a tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. It adds several features and a new clustering method (called, regional linkage) to hierarchical clustering in R ('hclust function in stats library): data regridding, coarsening spatial resolution, geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function with preliminary big data support, different clustering methods, hybrid hierarchical clustering, multivariate clustering (MVC), cluster validation, visualization of regionalization results, and exporting region map and mean timeseries into NetCDF-4 file. The technical details are described in Badr et al. (2015) <doi:10.1007/s12145-015-0221-7>.

r-hyper-fit 1.2.2
Propagated dependencies: r-rgl@1.3.31 r-mass@7.3-65 r-magicaxis@2.5.1 r-laplacesdemon@16.1.6
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hyper.fit
Licenses: GPL 3
Build system: r
Synopsis: N-Dimensional Hyperplane Fitting with Errors
Description:

High level functions for hyperplane fitting (hyper.fit()) and visualising (hyper.plot2d() / hyper.plot3d()). In simple terms this allows the user to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimension dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane.

r-hrtlfmc 0.1.0
Propagated dependencies: r-fmc@1.0.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hrtlFMC
Licenses: GPL 3
Build system: r
Synopsis: Half Replicate of Two Level Factorial Run Order with Minimum Level Changes
Description:

It is used to construct run sequences with minimum changes for half replicate of two level factorial run order. Experimenter can save time and resources by minimizing the number of changes in levels of individual factor and therefore the total number of changes. It consists of the function minimal_hrtlf(). This technique can be employed to any half replicate of two level factorial run order where the number of factors are greater than two. In Design of Experiments (DOE) theory, two level of a factor can be represented as integers e.g. - 1 for low and 1 for high. User is expected to enter total number of factors to be considered in the experiment. minimal_hrtlf() provides the required run sequences for the input number of factors. The output also gives the number of changes of each factor along with total number of changes in the run sequence. Due to restricted randomization the minimally changed run sequences of half replicate of two level factorial run order will be affected by trend effect. The output also provides the Trend Factor value of the run order. Trend factor value will lies between 0 to 1. Higher the values, lesser the influence of trend effects on the run order.

r-hamlet 0.9.8
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hamlet
Licenses: GPL 2+
Build system: r
Synopsis: Hierarchical Optimal Matching and Machine Learning Toolbox
Description:

Various functions and algorithms are provided here for solving optimal matching tasks in the context of preclinical cancer studies. Further, various helper and plotting functions are provided for unsupervised and supervised machine learning as well as longitudinal mixed-effects modeling of tumor growth response patterns.

r-hdmaadmm 0.0.1
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-dqrng@0.4.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/psyen0824/HDMAADMM
Licenses: Expat
Build system: r
Synopsis: ADMM for High-Dimensional Mediation Models
Description:

We use the Alternating Direction Method of Multipliers (ADMM) for parameter estimation in high-dimensional, single-modality mediation models. To improve the sensitivity and specificity of estimated mediation effects, we offer the sure independence screening (SIS) function for dimension reduction. The available penalty options include Lasso, Elastic Net, Pathway Lasso, and Network-constrained Penalty. The methods employed in the package are based on Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011). <doi:10.1561/2200000016>, Fan, J., & Lv, J. (2008) <doi:10.1111/j.1467-9868.2008.00674.x>, Li, C., & Li, H. (2008) <doi:10.1093/bioinformatics/btn081>, Tibshirani, R. (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, Zhao, Y., & Luo, X. (2022) <doi:10.4310/21-sii673>, and Zou, H., & Hastie, T. (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.

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-hctdesign 0.7.4
Propagated dependencies: r-survival@3.8-3 r-rdpack@2.6.4 r-mvtnorm@1.3-3 r-flexsurv@2.3.2 r-diversitree@0.10-1 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HCTDesign
Licenses: GPL 3
Build system: r
Synopsis: Group Sequential Design for Historical Control Trial with Survival Outcome
Description:

It provides functions to design historical controlled trials with survival outcome by group sequential method. The options for interim look boundaries are efficacy only, efficacy & futility or futility only. It also provides the function to monitor the trial for any unplanned look. The package is based on Jianrong Wu, Xiaoping Xiong (2016) <doi:10.1002/pst.1756> and Jianrong Wu, Yimei Li (2020) <doi:10.1080/10543406.2019.1684305>.

r-haldensify 0.2.8
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-scales@1.4.0 r-rlang@1.1.6 r-rdpack@2.6.4 r-origami@1.0.7 r-matrixstats@1.5.0 r-hal9001@0.4.6 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://codex.nimahejazi.org/haldensify/
Licenses: Expat
Build system: r
Synopsis: Highly Adaptive Lasso Conditional Density Estimation
Description:

An algorithm for flexible conditional density estimation based on application of pooled hazard regression to an artificial repeated measures dataset constructed by discretizing the support of the outcome variable. To facilitate flexible estimation of the conditional density, the highly adaptive lasso, a non-parametric regression function shown to estimate cadlag (RCLL) functions at a suitably fast convergence rate, is used. The use of pooled hazards regression for conditional density estimation as implemented here was first described for by DÃ az and van der Laan (2011) <doi:10.2202/1557-4679.1356>. Building on the conditional density estimation utilities, non-parametric inverse probability weighted (IPW) estimators of the causal effects of additive modified treatment policies are implemented, using conditional density estimation to estimate the generalized propensity score. Non-parametric IPW estimators based on this can be coupled with undersmoothing of the generalized propensity score estimator to attain the semi-parametric efficiency bound (per Hejazi, DÃ az, and van der Laan <doi:10.48550/arXiv.2205.05777>).

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