_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

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-spedm 1.9
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-sdsfun@0.8.1 r-rcppthread@2.2.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://stscl.github.io/spEDM/
Licenses: GPL 3
Synopsis: Spatial Empirical Dynamic Modeling
Description:

Inferring causation from spatial cross-sectional data through empirical dynamic modeling (EDM), with methodological extensions including geographical convergent cross mapping from Gao et al. (2023) <doi:10.1038/s41467-023-41619-6>, as well as the spatial causality test following the approach of Herrera et al. (2016) <doi:10.1111/pirs.12144>, together with geographical pattern causality proposed in Zhang et al. (2025) <doi:10.1080/13658816.2025.2581207>.

r-stors 1.0.1
Propagated dependencies: r-rlang@1.1.6 r-microbenchmark@1.5.0 r-digest@0.6.39 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://ahmad-alqabandi.github.io/stors/
Licenses: Expat
Synopsis: Step Optimised Rejection Sampling
Description:

Fast and efficient sampling from general univariate probability density functions. Implements a rejection sampling approach designed to take advantage of modern CPU caches and minimise evaluation of the target density for most samples. Many standard densities are internally implemented in C for high performance, with general user defined densities also supported. A paper describing the methodology will be released soon.

r-shapdoe 1.0.0
Propagated dependencies: r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=ShapDoE
Licenses: Expat
Synopsis: Approximation of the Shapley Values Based on Experimental Designs
Description:

Estimating the Shapley values using the algorithm in the paper Liuqing Yang, Yongdao Zhou, Haoda Fu, Min-Qian Liu and Wei Zheng (2024) <doi:10.1080/01621459.2023.2257364> "Fast Approximation of the Shapley Values Based on Order-of-Addition Experimental Designs". You provide the data and define the value function, it retures the estimated Shapley values based on sampling methods or experimental designs.

r-semnova 0.1-6
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=semnova
Licenses: GPL 2+
Synopsis: Latent Repeated Measures ANOVA
Description:

Latent repeated measures ANOVA (L-RM-ANOVA) is a structural equation modeling based alternative to traditional repeated measures ANOVA. L-RM-ANOVA extends the latent growth components approach by Mayer et al. (2012) <doi:10.1080/10705511.2012.713242> and introduces latent variables to repeated measures analysis.

r-sdchierarchies 0.22.0
Propagated dependencies: r-shinytree@0.3.1 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-rlang@1.1.6 r-rcpp@1.1.0 r-jsonlite@2.0.0 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/bernhard-da/sdcHierarchies
Licenses: GPL 3
Synopsis: Create and (Interactively) Modify Nested Hierarchies
Description:

This package provides functionality to generate, (interactively) modify (by adding, removing and renaming nodes) and convert nested hierarchies between different formats. These tree like structures can be used to define for example complex hierarchical tables used for statistical disclosure control.

r-survival-svb 0.0-2
Propagated dependencies: r-survival@3.8-3 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mkomod/survival.svb
Licenses: GPL 3
Synopsis: Fit High-Dimensional Proportional Hazards Models
Description:

Implementation of methodology designed to perform: (i) variable selection, (ii) effect estimation, and (iii) uncertainty quantification, for high-dimensional survival data. Our method uses a spike-and-slab prior with Laplace slab and Dirac spike and approximates the corresponding posterior using variational inference, a popular method in machine learning for scalable conditional inference. Although approximate, the variational posterior provides excellent point estimates and good control of the false discovery rate. For more information see Komodromos et al. (2021) <arXiv:2112.10270>.

r-stevedata 1.8.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://svmiller.com/stevedata/
Licenses: GPL 2
Synopsis: Steve's Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics
Description:

This is a collection of various kinds of data with broad uses for teaching. My students, and academics like me who teach the same topics I teach, should find this useful if their teaching workflow is also built around the R programming language. The applications are multiple but mostly cluster on topics of statistical methodology, international relations, and political economy.

r-shinylogs 0.2.1
Propagated dependencies: r-shiny@1.11.1 r-nanotime@0.3.12 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-digest@0.6.39 r-data-table@1.17.8 r-bit64@4.6.0-1 r-anytime@0.3.12
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/dreamRs/shinylogs
Licenses: GPL 3
Synopsis: Record Everything that Happens in a 'Shiny' Application
Description:

Track and record the use of applications and the user's interactions with Shiny inputs. Allows to trace the inputs with which the user interacts, the outputs generated, as well as the errors displayed in the interface.

r-slm 1.2.0
Propagated dependencies: r-sandwich@3.1-1 r-ltsa@1.4.6.1 r-expm@1.0-0 r-capushe@1.1.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=slm
Licenses: GPL 3
Synopsis: Stationary Linear Models
Description:

This package provides statistical procedures for linear regression in the general context where the errors are assumed to be correlated. Different ways to estimate the asymptotic covariance matrix of the least squares estimators are available. Starting from this estimation of the covariance matrix, the confidence intervals and the usual tests on the parameters are modified. The functions of this package are very similar to those of lm': it contains methods such as summary(), plot(), confint() and predict(). The slm package is described in the paper by E. Caron, J. Dedecker and B. Michel (2019), "Linear regression with stationary errors: the R package slm", arXiv preprint <arXiv:1906.06583>.

r-stochlab 1.1.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-pracma@2.4.6 r-msm@1.8.2 r-magrittr@2.0.4 r-logr@1.3.9 r-glue@1.8.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/HiDef-Aerial-Surveying/stochLAB
Licenses: GPL 3+
Synopsis: Stochastic Collision Risk Model
Description:

Collision Risk Models for avian fauna (seabird and migratory birds) at offshore wind farms. The base deterministic model is derived from Band (2012) <https://tethys.pnnl.gov/publications/using-collision-risk-model-assess-bird-collision-risks-offshore-wind-farms>. This was further expanded on by Masden (2015) <doi:10.7489/1659-1> and code used here is heavily derived from this work with input from Dr A. Cook at the British Trust for Ornithology. These collision risk models are useful for marine ornithologists who are working in the offshore wind industry, particularly in UK waters. However, many of the species included in the stochastic collision risk models can also be found in the North Atlantic in the United States and Canada, and could be applied there.

r-sparsecov 0.0.1
Propagated dependencies: r-sparsemvn@0.2.2 r-rfast@2.1.5.2 r-mvnfast@0.2.8 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/chexjiang/sparseCov
Licenses: GPL 2+
Synopsis: Sparse Covariance Estimation Based on Thresholding
Description:

This package provides a sparse covariance estimator based on different thresholding operators.

r-sihr 2.1.0
Propagated dependencies: r-glmnet@4.1-10 r-cvxr@1.0-15
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://zywang0701.github.io/SIHR/
Licenses: GPL 3
Synopsis: Statistical Inference in High Dimensional Regression
Description:

The goal of SIHR is to provide inference procedures in the high-dimensional generalized linear regression setting for: (1) linear functionals <doi:10.48550/arXiv.1904.12891> <doi:10.48550/arXiv.2012.07133>, (2) conditional average treatment effects, (3) quadratic functionals <doi:10.48550/arXiv.1909.01503>, (4) inner product, (5) distance.

r-spatialcovariance 0.6-9
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spatialCovariance
Licenses: GPL 2+ GPL 3+
Synopsis: Computation of Spatial Covariance Matrices for Data on Rectangles
Description:

This package provides functions that compute the spatial covariance matrix for the matern and power classes of spatial models, for data that arise on rectangular units. This code can also be used for the change of support problem and for spatial data that arise on irregularly shaped regions like counties or zipcodes by laying a fine grid of rectangles and aggregating the integrals in a form of Riemann integration.

r-srcs 1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://decsai.ugr.es/~pjvi/r-packages.html
Licenses: LGPL 3+
Synopsis: Statistical Ranking Color Scheme for Multiple Pairwise Comparisons
Description:

Implementation of the SRCS method for a color-based visualization of the results of multiple pairwise tests on a large number of problem configurations, proposed in: I.G. del Amo, D.A. Pelta. SRCS: a technique for comparing multiple algorithms under several factors in dynamic optimization problems. In: E. Alba, A. Nakib, P. Siarry (Eds.), Metaheuristics for Dynamic Optimization. Series: Studies in Computational Intelligence 433, Springer, Berlin/Heidelberg, 2012.

r-smdocker 0.1.4
Propagated dependencies: r-zip@2.3.3 r-uuid@1.2-1 r-paws-storage@0.9.0 r-paws-security-identity@0.9.0 r-paws-management@0.9.0 r-paws-machine-learning@0.9.0 r-paws-developer-tools@0.9.0 r-paws-compute@0.9.0 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/DyfanJones/sm-docker
Licenses: Expat
Synopsis: Build 'Docker Images' in 'Amazon SageMaker Studio' using 'Amazon Web Service CodeBuild'
Description:

Allows users to easily build custom docker images <https://docs.docker.com/> from Amazon Web Service Sagemaker <https://aws.amazon.com/sagemaker/> using Amazon Web Service CodeBuild <https://aws.amazon.com/codebuild/>.

r-shinyselect 1.3.0
Propagated dependencies: r-reactr@0.6.1 r-htmltools@0.5.8.1 r-fontawesome@0.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/stla/shinySelect
Licenses: GPL 3
Synopsis: Wrapper of the 'react-select' Library
Description:

This package provides a select control widget for Shiny'. It is easily customizable, and one can easily use HTML in the items and KaTeX to type mathematics.

r-spcp 1.4.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-msm@1.8.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spCP
Licenses: GPL 2+
Synopsis: Spatially Varying Change Points
Description:

This package implements a spatially varying change point model with unique intercepts, slopes, variance intercepts and slopes, and change points at each location. Inference is within the Bayesian setting using Markov chain Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget), probit or Tobit link and the five spatially varying parameter are modeled jointly using a multivariate conditional autoregressive (MCAR) prior. The MCAR is a unique process that allows for a dissimilarity metric to dictate the local spatial dependencies. Full details of the package can be found in the accompanying vignette. Furthermore, the details of the package can be found in the corresponding paper published in Spatial Statistics by Berchuck et al (2019): "A spatially varying change points model for monitoring glaucoma progression using visual field data", <doi:10.1016/j.spasta.2019.02.001>.

r-santoku 1.1.0
Propagated dependencies: r-vctrs@0.6.5 r-rlang@1.1.6 r-rcpp@1.1.0 r-lifecycle@1.0.4 r-glue@1.8.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/hughjonesd/santoku
Licenses: Expat
Synopsis: Versatile Cutting Tool
Description:

This package provides a tool for cutting data into intervals. Allows singleton intervals. Always includes the whole range of data by default. Flexible labelling. Convenience functions for cutting by quantiles etc. Handles dates, times, units and other vectors.

r-senspe 1.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SenSpe
Licenses: GPL 2+
Synopsis: Estimating Specificity at Controlled Sensitivity, or Vice Versa
Description:

Perform biomarker evaluation and comparison in terms of specificity at a controlled sensitivity level, or sensitivity at a controlled specificity level. Point estimation and exact bootstrap of Huang, Parakati, Patil, and Sanda (2023) <doi:10.5705/ss.202021.0020> for the one- and two-biomarker problems are implemented.

r-simplephenotypes 1.3.0
Propagated dependencies: r-snprelate@1.44.0 r-mvtnorm@1.3-3 r-gdsfmt@1.46.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/samuelbfernandes/simplePHENOTYPES
Licenses: Expat
Synopsis: Simulation of Pleiotropic, Linked and Epistatic Phenotypes
Description:

The number of studies involving correlated traits and the availability of tools to handle this type of data has increased considerably in the last decade. With such a demand, we need tools for testing hypotheses related to single and multi-trait (correlated) phenotypes based on many genetic settings. Thus, we implemented various options for simulation of pleiotropy and Linkage Disequilibrium under additive, dominance and epistatic models. The simulation currently takes a marker data set as an input and then uses it for simulating multiple traits as described in Fernandes and Lipka (2020) <doi:10.1186/s12859-020-03804-y>.

r-scitb 0.2.2
Propagated dependencies: r-stringi@1.8.7 r-reshape2@1.4.5 r-nortest@1.0-4 r-mass@7.3-65 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scitb
Licenses: GPL 3
Synopsis: Provides Some Useful Functions for Making Statistical Tables
Description:

You can use the functions provided by the package to make various statistical tables, such as baseline data tables. Creates Table 1', i.e., a description of the baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. This method was described by Mary L McHugh (2013) <doi:10.11613/bm.2013.018>.

r-scgwr 0.1.2-21
Propagated dependencies: r-spdata@2.3.4 r-sp@2.2-0 r-optimparallel@1.0-2 r-fnn@1.1.4.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scgwr
Licenses: GPL 2+
Synopsis: Scalable Geographically Weighted Regression
Description:

Fast and regularized version of GWR for large dataset, detailed in Murakami, Tsutsumida, Yoshida, Nakaya, and Lu (2019) <arXiv:1905.00266>.

r-specklestar 0.0.1.7
Dependencies: fftw@3.3.10
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://drastega.github.io/docs/specklestar_vignette.html
Licenses: GPL 2
Synopsis: Reduction of Speckle Data from BTA 6-m Telescope
Description:

This package provides a set of functions for obtaining positional parameters and magnitude difference between components of binary and multiple stellar systems from series of speckle images.

r-sis 0.8-8
Propagated dependencies: r-survival@3.8-3 r-ncvreg@3.16.0 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SIS
Licenses: GPL 2
Synopsis: Sure Independence Screening
Description:

Variable selection techniques are essential tools for model selection and estimation in high-dimensional statistical models. Through this publicly available package, we provide a unified environment to carry out variable selection using iterative sure independence screening (SIS) (Fan and Lv (2008)<doi:10.1111/j.1467-9868.2008.00674.x>) and all of its variants in generalized linear models (Fan and Song (2009)<doi:10.1214/10-AOS798>) and the Cox proportional hazards model (Fan, Feng and Wu (2010)<doi:10.1214/10-IMSCOLL606>).

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Total results: 68249