_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-hazarddiff 0.1.0
Propagated dependencies: r-survival@3.8-3 r-rootsolve@1.8.2.4 r-rdpack@2.6.4 r-ahaz@1.15.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HazardDiff
Licenses: GPL 2
Build system: r
Synopsis: Conditional Treatment Effect for Competing Risks
Description:

The conditional treatment effect for competing risks data in observational studies is estimated. While it is described as a constant difference between the hazard functions given the covariates, we do not assume specific functional forms for the covariates. Rava, D. and Xu, R. (2021) <arXiv:2112.09535>.

r-hcmodelsets 1.1.3
Propagated dependencies: r-survival@3.8-3 r-mvtnorm@1.3-3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HCmodelSets
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Regression with a Large Number of Potential Explanatory Variables
Description:

Software for performing the reduction, exploratory and model selection phases of the procedure proposed by Cox, D.R. and Battey, H.S. (2017) <doi:10.1073/pnas.1703764114> for sparse regression when the number of potential explanatory variables far exceeds the sample size. The software supports linear regression, likelihood-based fitting of generalized linear regression models and the proportional hazards model fitted by partial likelihood.

r-heiscore-data 0.0.1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=heiscore.data
Licenses: CC0
Build system: r
Synopsis: Data Only Package to 'heiscore'
Description:

This package contains the National Health and Nutrition Examination Survey 24-hour dietary recall data and Healthy Eating Index scoring standards used by the heiscore package.

r-hyperbolicdea 1.0.2
Propagated dependencies: r-nloptr@2.2.1 r-lpsolveapi@5.5.2.0-17.14 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-benchmarking@0.33
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=hyperbolicDEA
Licenses: Expat
Build system: r
Synopsis: Hyperbolic DEA Estimation
Description:

This package implements Data Envelopment Analysis (DEA) with a hyperbolic orientation using a non-linear programming solver. It enables flexible estimations with weight restrictions, non-discretionary variables, and a generalized distance function. Additionally, it allows for the calculation of slacks and super-efficiency scores. The methods are detailed in à ttl et al. (2023), <doi:10.1016/j.dajour.2023.100343>. Furthermore, the package provides a non-linear profitability estimation built upon the DEA framework.

r-hfr 0.7.1
Propagated dependencies: r-rcolorbrewer@1.1-3 r-quadprog@1.5-8 r-dendextend@1.19.1 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://hfr.residualmetrics.com
Licenses: GPL 2
Build system: r
Synopsis: Estimate Hierarchical Feature Regression Models
Description:

This package provides functions for the estimation, plotting, predicting and cross-validation of hierarchical feature regression models as described in Pfitzinger (2024). Cluster Regularization via a Hierarchical Feature Regression. Econometrics and Statistics (in press). <doi:10.1016/j.ecosta.2024.01.003>.

r-hbsaems 0.1.1
Propagated dependencies: r-xicor@0.4.1 r-shinywidgets@0.9.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-readxl@1.4.5 r-priorsense@1.2.0 r-posterior@1.6.1 r-minerva@1.5.10 r-mice@3.18.0 r-ggplot2@4.0.1 r-energy@1.7-12 r-dt@0.34.0 r-coda@0.19-4.1 r-brms@2.23.0 r-bridgesampling@1.2-1 r-bayesplot@1.14.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/madsyair/hbsaems
Licenses: GPL 3+
Build system: r
Synopsis: Hierarchical Bayes Small Area Estimation Model using 'Stan'
Description:

Implementing Hierarchical Bayesian Small Area Estimation models using the brms package as the computational backend. The modeling framework follows the methodological foundations described in area-level models. This package is designed to facilitate a principled Bayesian workflow, enabling users to conduct prior predictive checks, model fitting, posterior predictive checks, model comparison, and sensitivity analysis in a coherent and reproducible manner. It supports flexible model specifications via brms and promotes transparency in model development, aligned with the recommendations of modern Bayesian data analysis practices, implementing methods described in Rao and Molina (2015) <doi:10.1002/9781118735855>.

r-hbamr 2.4.4
Propagated dependencies: r-tidyr@1.3.1 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rlang@1.1.6 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-progressr@0.18.0 r-plyr@1.8.9 r-matrixstats@1.5.0 r-loo@2.8.0 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0 r-dplyr@1.1.4 r-colorspace@2.1-2 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://jbolstad.github.io/hbamr/
Licenses: GPL 3+
Build system: r
Synopsis: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'
Description:

Perform hierarchical Bayesian Aldrich-McKelvey scaling using Hamiltonian Monte Carlo via Stan'. Aldrich-McKelvey ('AM') scaling is a method for estimating the ideological positions of survey respondents and political actors on a common scale using positional survey data. The hierarchical versions of the Bayesian AM model included in this package outperform other versions both in terms of yielding meaningful posterior distributions for respondent positions and in terms of recovering true respondent positions in simulations. The package contains functions for preparing data, fitting models, extracting estimates, plotting key results, and comparing models using cross-validation. The original version of the default model is described in Bølstad (2024) <doi:10.1017/pan.2023.18>.

r-handwriterrf 1.1.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringr@1.6.0 r-reshape2@1.4.5 r-ranger@0.17.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-handwriter@3.2.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/CSAFE-ISU/handwriterRF
Licenses: GPL 3+
Build system: r
Synopsis: Handwriting Analysis with Random Forests
Description:

Perform forensic handwriting analysis of two scanned handwritten documents. This package implements the statistical method described by Madeline Johnson and Danica Ommen (2021) <doi:10.1002/sam.11566>. Similarity measures and a random forest produce a score-based likelihood ratio that quantifies the strength of the evidence in favor of the documents being written by the same writer or different writers.

r-hgmnd 0.1.0
Propagated dependencies: r-genscore@1.0.2.2
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HGMND
Licenses: GPL 3
Build system: r
Synopsis: Heterogeneous Graphical Model for Non-Negative Data
Description:

Graphical model is an informative and powerful tool to explore the conditional dependence relationships among variables. The traditional Gaussian graphical model and its extensions either have a Gaussian assumption on the data distribution or assume the data are homogeneous. However, there are data with complex distributions violating these two assumptions. For example, the air pollutant concentration records are non-negative and, hence, non-Gaussian. Moreover, due to climate changes, distributions of these concentration records in different months of a year can be far different, which means it is uncertain whether datasets from different months are homogeneous. Methods with a Gaussian or homogeneous assumption may incorrectly model the conditional dependence relationships among variables. Therefore, we propose a heterogeneous graphical model for non-negative data (HGMND) to simultaneously cluster multiple datasets and estimate the conditional dependence matrix of variables from a non-Gaussian and non-negative exponential family in each cluster.

r-hts 6.0.3
Propagated dependencies: r-sparsem@1.84-2 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-matrix@1.7-4 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://pkg.earo.me/hts/
Licenses: GPL 2+
Build system: r
Synopsis: Hierarchical and Grouped Time Series
Description:

This package provides methods for analysing and forecasting hierarchical and grouped time series. The available forecast methods include bottom-up, top-down, optimal combination reconciliation (Hyndman et al. 2011) <doi:10.1016/j.csda.2011.03.006>, and trace minimization reconciliation (Wickramasuriya et al. 2018) <doi:10.1080/01621459.2018.1448825>.

r-harvest-tree 1.1
Propagated dependencies: r-rpart@4.1.24
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=Harvest.Tree
Licenses: GPL 2
Build system: r
Synopsis: Harvest the Classification Tree
Description:

Aimed at applying the Harvest classification tree algorithm, modified algorithm of classic classification tree.The harvested tree has advantage of deleting redundant rules in trees, leading to a simplify and more efficient tree model.It was firstly used in drug discovery field, but it also performs well in other kinds of data, especially when the region of a class is disconnected. This package also improves the basic harvest classification tree algorithm by extending the field of data of algorithm to both continuous and categorical variables. To learn more about the harvest classification tree algorithm, you can go to http://www.stat.ubc.ca/Research/TechReports/techreports/220.pdf for more information.

r-hhp 1.0.0
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://cran.r-project.org/package=HhP
Licenses: GPL 2
Build system: r
Synopsis: Hierarchical Heterogeneity Analysis via Penalization
Description:

In medical research, supervised heterogeneity analysis has important implications. Assume that there are two types of features. Using both types of features, our goal is to conduct the first supervised heterogeneity analysis that satisfies a hierarchical structure. That is, the first type of features defines a rough structure, and the second type defines a nested and more refined structure. A penalization approach is developed, which has been motivated by but differs significantly from penalized fusion and sparse group penalization. Reference: Ren, M., Zhang, Q., Zhang, S., Zhong, T., Huang, J. & Ma, S. (2022). "Hierarchical cancer heterogeneity analysis based on histopathological imaging features". Biometrics, <doi:10.1111/biom.13426>.

r-htlr 1.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-magrittr@2.0.4 r-glmnet@4.1-10 r-bcbcsf@1.0-1
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>.

r-hlmdiag 0.5.1
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-reshape2@1.4.5 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-plyr@1.8.9 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-janitor@2.2.1 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-diagonals@6.4.0
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/aloy/HLMdiag
Licenses: GPL 2
Build system: r
Synopsis: Diagnostic Tools for Hierarchical (Multilevel) Linear Models
Description:

This package provides a suite of diagnostic tools for hierarchical (multilevel) linear models. The tools include not only leverage and traditional deletion diagnostics (Cook's distance, covratio, covtrace, and MDFFITS) but also convenience functions and graphics for residual analysis. Models can be fit using either lmer in the lme4 package or lme in the nlme package.

r-hspor 1.1.9
Propagated dependencies: r-npregfast@1.6.0 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HSPOR
Licenses: LGPL 3
Build system: r
Synopsis: Hidden Smooth Polynomial Regression for Rupture Detection
Description:

Several functions that allow by different methods to infer a piecewise polynomial regression model under regularity constraints, namely continuity or differentiability of the link function. The implemented functions are either specific to data with two regimes, or generic for any number of regimes, which can be given by the user or learned by the algorithm. A paper describing all these methods will be submitted soon. The reference will be added to this file as soon as available.

r-higarrote 2.0.0
Propagated dependencies: r-stringr@1.6.0 r-scales@1.4.0 r-rlist@0.4.6.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-quadprog@1.5-8 r-purrr@1.2.0 r-nloptr@2.2.1 r-maxpro@4.1-2 r-matrixcalc@1.0-6 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=HiGarrote
Licenses: GPL 2+
Build system: r
Synopsis: Nonnegative Garrote Method Incorporating Hierarchical Relationships
Description:

An implementation of the nonnegative garrote method that incorporates hierarchical relationships among variables. The core function, HiGarrote(), offers an automated approach for analyzing experiments while respecting hierarchical structures among effects. For methodological details, refer to Yu and Joseph (2025) <doi:10.1080/00224065.2025.2513508>. This work is supported by U.S. National Science Foundation grant DMS-2310637.

r-hodgestools 1.0.0
Propagated dependencies: r-recordlinkage@0.4-12.6 r-readr@2.1.6 r-rcolorbrewer@1.1-3 r-qqman@0.1.9 r-magrittr@2.0.4 r-ini@0.3.1 r-ggplot2@4.0.1 r-dplyr@1.1.4 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=HodgesTools
Licenses: GPL 3+
Build system: r
Synopsis: Common Use Tools for Genomic Analysis
Description:

Built by Hodges lab members for current and future Hodges lab members. Other individuals are welcome to use as well. Provides useful functions that the lab uses everyday to analyze various genomic datasets. Critically, only general use functions are provided; functions specific to a given technique are reserved for a separate package. As the lab grows, we expect to continue adding functions to the package to build on previous lab members code.

r-hima 2.3.3
Propagated dependencies: r-survival@3.8-3 r-quantreg@6.1 r-nlme@3.1-168 r-ncvreg@3.16.0 r-mass@7.3-65 r-iterators@1.0.14 r-hommel@1.8 r-hdmt@1.0.5 r-hdi@0.1-10 r-glmnet@4.1-10 r-foreach@1.5.2 r-doparallel@1.0.17 r-conquer@1.3.3
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/YinanZheng/HIMA/
Licenses: GPL 3
Build system: r
Synopsis: High-Dimensional Mediation Analysis
Description:

Allows to estimate and test high-dimensional mediation effects based on advanced mediator screening and penalized regression techniques. Methods used in the package refer to Zhang H, Zheng Y, Hou L, Liu L, HIMA: An R Package for High-Dimensional Mediation Analysis. Journal of Data Science. (2025). <doi:10.6339/25-JDS1192>.

r-howler 0.3.0
Propagated dependencies: r-shiny@1.11.1 r-htmlwidgets@1.6.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/ashbaldry/howler
Licenses: Expat
Build system: r
Synopsis: 'Shiny' Extension of 'howler.js'
Description:

Audio interactivity within shiny applications using howler.js'. Enables the status of the audio player to be sent from the UI to the server, and events such as playing and pausing the audio can be triggered from the server.

r-hydroloom 1.1.1
Propagated dependencies: r-units@1.0-0 r-tidyr@1.3.1 r-sf@1.0-23 r-rlang@1.1.6 r-rann@2.6.2 r-pbapply@1.7-4 r-fastmap@1.2.0 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://github.com/DOI-USGS/hydroloom
Licenses: CC0
Build system: r
Synopsis: Utilities to Weave Hydrologic Fabrics
Description:

This package provides a collection of utilities that support creation of network attributes for hydrologic networks. Methods and algorithms implemented are documented in Moore et al. (2019) <doi:10.3133/ofr20191096>), Cormen and Leiserson (2022) <ISBN:9780262046305> and Verdin and Verdin (1999) <doi:10.1016/S0022-1694(99)00011-6>.

r-hsaur 1.3-11
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://cran.r-project.org/package=HSAUR
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Handbook of Statistical Analyses Using R (1st Edition)
Description:

Functions, data sets, analyses and examples from the book A Handbook of Statistical Analyses Using R (Brian S. Everitt and Torsten Hothorn, Chapman & Hall/CRC, 2006). The first chapter of the book, which is entitled An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available.

r-headliner 0.0.3
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-lubridate@1.9.4 r-glue@1.8.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://rjake.github.io/headliner/
Licenses: Expat
Build system: r
Synopsis: Compose Sentences to Describe Comparisons
Description:

Create dynamic, data-driven text. Given two values, a list of talking points is generated and can be combined using string interpolation. Based on the glue package.

r-historicalborrowlong 0.1.0
Propagated dependencies: r-zoo@1.8-14 r-withr@3.0.2 r-trialr@0.1.6 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rlang@1.1.6 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-posterior@1.6.1 r-matrix@1.7-4 r-mass@7.3-65 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-clustermq@0.9.9 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/h.scm (guix-cran packages h)
Home page: https://wlandau.github.io/historicalborrowlong/
Licenses: Expat
Build system: r
Synopsis: Longitudinal Bayesian Historical Borrowing Models
Description:

Historical borrowing in clinical trials can improve precision and operating characteristics. This package supports a longitudinal hierarchical model to borrow historical control data from other studies to better characterize the control response of the current study. It also quantifies the amount of borrowing through longitudinal benchmark models (independent and pooled). The hierarchical model approach to historical borrowing is discussed by Viele et al. (2013) <doi:10.1002/pst.1589>.

r-hvt 26.1.2
Propagated dependencies: r-umap@0.2.10.0 r-tidyr@1.3.1 r-splancs@2.01-45 r-scales@1.4.0 r-rtsne@0.17 r-reshape2@1.4.5 r-purrr@1.2.0 r-plyr@1.8.9 r-nbclust@3.0.1 r-mass@7.3-65 r-markovchain@0.10.3 r-magrittr@2.0.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-fnn@1.1.4.1 r-dplyr@1.1.4 r-deldir@2.0-4 r-cluster@2.1.8.1
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.

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Total results: 68658