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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-hcuptools 1.0.0
Propagated dependencies: r-xml2@1.5.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-readxl@1.4.5 r-readr@2.1.6 r-httr2@1.2.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/vikrant31/HCUPtools
Licenses: Expat
Build system: r
Synopsis: Access and Work with HCUP Resources and Datasets
Description:

This package provides a comprehensive R package for accessing and working with publicly available and free resources from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP). The package provides streamlined access to HCUP's Clinical Classifications Software Refined (CCSR) mapping files and Summary Trend Tables, enabling researchers and analysts to efficiently map ICD-10-CM diagnosis codes and ICD-10-PCS procedure codes to CCSR categories and access HCUP statistical reports. Key features include: direct download from HCUP website, multiple output formats (long/wide/default), cross-classification support, version management, citation generation, and intelligent caching. The package does not redistribute HCUP data files but facilitates direct download from the official HCUP website, ensuring users always have access to the latest versions and maintain compliance with HCUP data use policies. This package only accesses free public tools and reports; it does NOT access HCUP databases (NIS, KID, SID, NEDS, etc.) that require purchase. For more information, see <https://hcup-us.ahrq.gov/>.

r-hmmextra0s 1.1.0
Propagated dependencies: r-mvtnorm@1.3-3 r-ellipse@0.5.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://www.stats.otago.ac.nz/?people=ting_wang
Licenses: GPL 2+
Build system: r
Synopsis: Hidden Markov Models with Extra Zeros
Description:

This package contains functions for hidden Markov models with observations having extra zeros as defined in the following two publications, Wang, T., Zhuang, J., Obara, K. and Tsuruoka, H. (2016) <doi:10.1111/rssc.12194>; Wang, T., Zhuang, J., Buckby, J., Obara, K. and Tsuruoka, H. (2018) <doi:10.1029/2017JB015360>. The observed response variable is either univariate or bivariate Gaussian conditioning on presence of events, and extra zeros mean that the response variable takes on the value zero if nothing is happening. Hence the response is modelled as a mixture distribution of a Bernoulli variable and a continuous variable. That is, if the Bernoulli variable takes on the value 1, then the response variable is Gaussian, and if the Bernoulli variable takes on the value 0, then the response is zero too. This package includes functions for simulation, parameter estimation, goodness-of-fit, the Viterbi algorithm, and plotting the classified 2-D data. Some of the functions in the package are based on those of the R package HiddenMarkov by David Harte. This updated version has included an example dataset and R code examples to show how to transform the data into the objects needed in the main functions. We have also made changes to increase the speed of some of the functions.

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-harmonizer 0.3.2
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=harmonizer
Licenses: GPL 3+
Build system: r
Synopsis: Harmonizing CN8 and PC8 Product Codes
Description:

Several functions are provided to harmonize CN8 (Combined Nomenclature 8 digits) and PC8 (Production Communautaire 8 digits) product codes over time and the classification systems HS6 and BEC. Harmonization of CN8 codes are possible by default from 1995 to 2022 and of PC8 from 2001 to 2021, respectively.

r-haplocatcher 1.0.4
Propagated dependencies: r-randomforest@4.7-1.2 r-patchwork@1.3.2 r-lattice@0.22-7 r-knitr@1.50 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HaploCatcher
Licenses: Expat
Build system: r
Synopsis: Predictive Haplotyping Package
Description:

Used for predicting a genotypeâ s allelic state at a specific locus/QTL/gene. This is accomplished by using both a genotype matrix and a separate file which has categorizations about loci/QTL/genes of interest for the individuals in the genotypic matrix. A training population can be created from a panel of individuals who have been previously screened for specific loci/QTL/genes, and this previous screening could be summarized into a category. Using the categorization of individuals which have been genotyped using a genome wide marker platform, a model can be trained to predict what category (haplotype) an individual belongs in based on their genetic sequence in the region associated with the locus/QTL/gene. These trained models can then be used to predict the haplotype of a locus/QTL/gene for individuals which have been genotyped with a genome wide platform yet not genotyped for the specific locus/QTL/gene. This package is based off work done by Winn et al 2021. For more specific information on this method, refer to <doi:10.1007/s00122-022-04178-w>.

r-hrqglas 1.1.2
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/shaobo-li/hrqglas
Licenses: GPL 2+
Build system: r
Synopsis: Group Variable Selection for Quantile and Robust Mean Regression
Description:

This package provides a program that conducts group variable selection for quantile and robust mean regression (Sherwood and Li, 2022). The group lasso penalty (Yuan and Lin, 2006) is used for group-wise variable selection. Both of the quantile and mean regression models are based on the Huber loss. Specifically, with the tuning parameter in the Huber loss approaching to 0, the quantile check function can be approximated by the Huber loss for the median and the tilted version of Huber loss at other quantiles. Such approximation provides computational efficiency and stability, and has also been shown to be statistical consistent.

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-haplotypes 1.1.3.2
Propagated dependencies: r-sna@2.8 r-plotrix@3.8-13 r-phangorn@2.12.1 r-network@1.19.0 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=haplotypes
Licenses: GPL 2
Build system: r
Synopsis: Manipulating DNA Sequences and Estimating Unambiguous Haplotype Network with Statistical Parsimony
Description:

This package provides S4 classes and methods for reading and manipulating aligned DNA sequences, supporting an indel-coding method (only simple indel-coding method is available in the current version), showing base substitutions and indels, calculating absolute pairwise distances between DNA sequences, and collapsing identical DNA sequences into haplotypes or inferring haplotypes using user-provided absolute pairwise character difference matrix. This package also includes S4 classes and methods for estimating genealogical relationships among haplotypes using statistical parsimony and plotting parsimony networks.

r-hettest 1.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hettest
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Testing for a Treatment Effect Using a Heterogeneous Surrogate Marker
Description:

Tests for a treatment effect using surrogate marker information accounting for heterogeneity in the utility of the surrogate. Details are described in Parast et al (2022) <arXiv:2209.08315>.

r-holland 0.1.2-4
Propagated dependencies: r-mvtnorm@1.3-3 r-mplusautomation@1.2
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=holland
Licenses: GPL 3
Build system: r
Synopsis: Statistics for Holland's Theory of Vocational Choice
Description:

Offers a convenient way to compute parameters in the framework of the theory of vocational choice introduced by J.L. Holland, (1997). A comprehensive summary to this theory of vocational choice is given in Holland, J.L. (1997). Making vocational choices. A theory of vocational personalities and work environments. Lutz, FL: Psychological Assessment.

r-hyperoverlap 1.1.4
Propagated dependencies: r-rgl@1.3.31 r-misc3d@0.9-1 r-matlib@1.0.1 r-mass@7.3-65 r-ggplot2@4.0.1 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hyperoverlap
Licenses: GPL 3
Build system: r
Synopsis: Overlap Detection in n-Dimensional Space
Description:

Uses support vector machines to identify a perfectly separating hyperplane (linear or curvilinear) between two entities in high-dimensional space. If this plane exists, the entities do not overlap. Applications include overlap detection in morphological, resource or environmental dimensions. More details can be found in: Brown et al. (2020) <doi:10.1111/2041-210X.13363> .

r-hac 1.1-2
Propagated dependencies: r-copula@1.1-6
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://tu-dresden.de/bu/verkehr/ivw/osv/die-professur/inhaber-in
Licenses: GPL 3+
Build system: r
Synopsis: Estimation, Simulation and Visualization of Hierarchical Archimedean Copulae (HAC)
Description:

Package provides the estimation of the structure and the parameters, sampling methods and structural plots of Hierarchical Archimedean Copulae (HAC).

r-hellno 0.0.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/petermeissner/hellno
Licenses: Expat
Build system: r
Synopsis: Providing 'stringsAsFactors=FALSE' Variants of 'data.frame()' and 'as.data.frame()'
Description:

Base R's default setting for stringsAsFactors within data.frame() and as.data.frame() is supposedly the most often complained about piece of code in the R infrastructure. The hellno package provides an explicit solution without changing R itself or having to mess around with options. It tries to solve this problem by providing alternative data.frame() and as.data.frame() functions that are in fact simple wrappers around base R's data.frame() and as.data.frame() with stringsAsFactors option set to HELLNO ( which in turn equals FALSE ) by default.

r-hcci 1.2.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/prdm0/hcci
Licenses: GPL 3+
Build system: r
Synopsis: Interval Estimation of Linear Models with Heteroskedasticity
Description:

Calculates the interval estimates for the parameters of linear models with heteroscedastic regression using bootstrap - (Wild Bootstrap) and double bootstrap-t (Wild Bootstrap). It is also possible to calculate confidence intervals using the percentile bootstrap and percentile bootstrap double. The package can calculate consistent estimates of the covariance matrix of the parameters of linear regression models with heteroscedasticity of unknown form. The package also provides a function to consistently calculate the covariance matrix of the parameters of linear models with heteroscedasticity of unknown form. The bootstrap methods exported by the package are based on the master's thesis of the first author, available at <https://raw.githubusercontent.com/prdm0/hcci/master/references/dissertacao_mestrado.pdf>. The hcci package in previous versions was cited in the book VINOD, Hrishikesh D. Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software. 2022, p. 441, ISBN 978-981-125-617-2 (hardcover). The simple bootstrap schemes are based on the works of Cribari-Neto F and Lima M. G. (2009) <doi:10.1080/00949650801935327>, while the double bootstrap schemes for the parameters that index the linear models with heteroscedasticity of unknown form are based on the works of Beran (1987) <doi:10.2307/2336685>. The use of bootstrap for the calculation of interval estimates in regression models with heteroscedasticity of unknown form from a weighting of the residuals was proposed by Wu (1986) <doi:10.1214/aos/1176350142>. This bootstrap scheme is known as weighted or wild bootstrap.

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-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-hydrocal 1.0.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: GitHub
Licenses: GPL 3
Build system: r
Synopsis: Hydraulic Roughness Calculator
Description:

Estimates frictional constants for hydraulic analysis of rivers. This HYDRaulic ROughness CALculator (HYDROCAL) was previously developed as a spreadsheet tool and accompanying documentation by McKay and Fischenich (2011, <https://erdc-library.erdc.dren.mil/jspui/bitstream/11681/2034/1/CHETN-VII-11.pdf>).

r-hglm 2.2-1
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-hglm-data@1.0-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hglm
Licenses: GPL 2+
Build system: r
Synopsis: Hierarchical Generalized Linear Models
Description:

Implemented here are procedures for fitting hierarchical generalized linear models (HGLM). It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the mean model. As statistical models, HGLMs were initially developed by Lee and Nelder (1996) <https://www.jstor.org/stable/2346105?seq=1>. We provide an implementation (Ronnegard, Alam and Shen 2010) <https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Roennegaard~et~al.pdf> following Lee, Nelder and Pawitan (2006) <ISBN: 9781420011340> with algorithms extended for spatial modeling (Alam, Ronnegard and Shen 2015) <https://journal.r-project.org/archive/2015/RJ-2015-017/RJ-2015-017.pdf>.

r-hdtg 0.3.4
Propagated dependencies: r-rdpack@2.6.4 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hdtg
Licenses: Expat
Build system: r
Synopsis: Generate Samples from Multivariate Truncated Normal Distributions
Description:

Efficient sampling from high-dimensional truncated Gaussian distributions, or multivariate truncated normal (MTN). Techniques include zigzag Hamiltonian Monte Carlo as in Akihiko Nishimura, Zhenyu Zhang and Marc A. Suchard (2024) <doi:10.1080/01621459.2024.2395587>, and harmonic Monte Carlo in Ari Pakman and Liam Paninski (2014) <doi:10.1080/10618600.2013.788448>.

r-hakaiapi 1.0.5
Propagated dependencies: r-tibble@3.3.0 r-readr@2.1.6 r-r6@2.6.1 r-httr2@1.2.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/HakaiInstitute/hakai-api-client-r
Licenses: Expat
Build system: r
Synopsis: Authenticated HTTP Request Client for the 'Hakai' API
Description:

Initializes a class that obtains API credentials and provides a method to use those credentials to make GET requests to the Hakai API server. Usage instructions are documented at <https://hakaiinstitute.github.io/hakai-api/>.

r-hqmisc 0.2-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hqmisc
Licenses: GPL 2+
Build system: r
Synopsis: Miscellaneous Convenience Functions and Dataset
Description:

Miscellaneous convenience functions and wrapper functions to convert frequencies between Hz, semitones, mel and Bark, to create a matrix of dummy columns from a factor, to determine whether x lies in range [a,b], and to add a bracketed line to an existing plot. This package also contains an example data set of a stratified sample of 80 talkers of Dutch.

r-haplo-ccs 1.3.3
Propagated dependencies: r-survival@3.8-3 r-haplo-stats@1.9.7
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/vubiostat/haplo.ccs
Licenses: GPL 2+
Build system: r
Synopsis: Estimate Haplotype Relative Risks in Case-Control Data
Description:

Haplotype and covariate relative risks in case-control data are estimated by weighted logistic regression. Diplotype probabilities, which are estimated by EM computation with progressive insertion of loci, are utilized as weights. French et al. (2006) <doi:10.1002/gepi.20161>.

r-harr 1.1.0
Propagated dependencies: r-stringi@1.8.7
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HARr
Licenses: CC0
Build system: r
Synopsis: 'HAR' ('GEMPACK') File Read/Write Utility
Description:

HAR files are generated and consumed by GEMPACK applications. This package reads/writes HAR files (and SL4 files) directly using basic R functions.

r-hspm 1.1
Propagated dependencies: r-sphet@2.1-1 r-spdep@1.4-1 r-matrix@1.7-4 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/gpiras/hspm
Licenses: GPL 2+
Build system: r
Synopsis: Heterogeneous Spatial Models
Description:

Spatial heterogeneity can be specified in various ways. hspm is an ambitious project that aims at implementing various methodologies to control for heterogeneity in spatial models. The current version of hspm deals with spatial and (non-spatial) regimes models. In particular, the package allows to estimate a general spatial regimes model with additional endogenous variables, specified in terms of a spatial lag of the dependent variable, the spatially lagged regressors, and, potentially, a spatially autocorrelated error term. Spatial regime models are estimated by instrumental variables and generalized methods of moments (see Arraiz et al., (2010) <doi:10.1111/j.1467-9787.2009.00618.x>, Bivand and Piras, (2015) <doi:10.18637/jss.v063.i18>, Drukker et al., (2013) <doi:10.1080/07474938.2013.741020>, Kelejian and Prucha, (2010) <doi:10.1016/j.jeconom.2009.10.025>).

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