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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-simplicialcomplex 0.1.0
Propagated dependencies: r-matrix@1.7-4 r-igraph@2.2.1 r-gtools@3.9.5 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/TDA-R/SimplicialComplex
Licenses: Expat
Build system: r
Synopsis: Topological Data Analysis: Simplicial Complex
Description:

This package provides an implementation of simplicial complexes for Topological Data Analysis (TDA). The package includes functions to compute faces, boundary operators, Betti numbers, Euler characteristic, and to construct simplicial complexes. It also implements persistent homology, from building filtrations to computing persistence diagrams, with the aim of helping readers understand the core concepts of computational topology. Methods are based on standard references in persistent homology such as Zomorodian and Carlsson (2005) <doi:10.1007/s00454-004-1146-y> and Chazal and Michel (2021) <doi:10.3389/frai.2021.667963>.

r-stressstrength 1.0.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=StressStrength
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Computation and Estimation of Reliability of Stress-Strength Models
Description:

Reliability of (normal) stress-strength models and for building two-sided or one-sided confidence intervals according to different approximate procedures.

r-sandbox 0.2.2
Propagated dependencies: r-rlummodel@0.2.11
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sandbox
Licenses: GPL 3
Build system: r
Synopsis: Probabilistic Numerical Modelling of Sediment Properties
Description:

This package provides a flexible framework for definition and application of time/depth- based rules for sets of parameters for single grains that can be used to create artificial sediment profiles. Such profiles can be used for virtual sample preparation and synthetic, for instance, luminescence measurements.

r-stratus 1.1.2
Propagated dependencies: r-rcppalgos@2.9.3 r-phangorn@2.12.1 r-igraph@2.2.1 r-gmp@0.7-5 r-ggtree@4.0.1 r-ggplot2@4.0.1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://github.com/mdhall272/STraTUS/
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Enumeration and Uniform Sampling of Transmission Trees for a Known Phylogeny
Description:

For a single, known pathogen phylogeny, provides functions for enumeration of the set of compatible epidemic transmission trees, and for uniform sampling from that set. Optional arguments allow for incomplete sampling with a known number of missing individuals, multiple sampling, and known infection time limits. Always assumed are a complete transmission bottleneck and no superinfection or reinfection. See Hall and Colijn (2019) <doi:10.1093/molbev/msz058> for methodology.

r-stepwisetest 1.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=StepwiseTest
Licenses: GPL 2+
Build system: r
Synopsis: Multiple Testing Method to Control Generalized Family-Wise Error Rate and False Discovery Proportion
Description:

Collection of stepwise procedures to conduct multiple hypotheses testing. The details of the stepwise algorithm can be found in Romano and Wolf (2007) <DOI:10.1214/009053606000001622> and Hsu, Kuan, and Yen (2014) <DOI:10.1093/jjfinec/nbu014>.

r-sicure 0.1.1
Propagated dependencies: r-statmatch@1.4.3 r-npcure@0.1-5 r-fda@6.3.0 r-doby@4.7.0 r-catools@1.18.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sicure
Licenses: GPL 2+
Build system: r
Synopsis: Single-Index Mixture Cure Models
Description:

Single-index mixture cure models allow estimating the probability of cure and the latency depending on a vector (or functional) covariate, avoiding the curse of dimensionality. The vector of parameters that defines the model can be estimated by maximum likelihood. A nonparametric estimator for the conditional density of the susceptible population is provided. For more details, see Piñeiro-Lamas (2024) (<https://ruc.udc.es/dspace/handle/2183/37035>). Funding: This work, integrated into the framework of PERTE for Vanguard Health, has been co-financed by the Spanish Ministry of Science, Innovation and Universities with funds from the European Union NextGenerationEU, from the Recovery, Transformation and Resilience Plan (PRTR-C17.I1) and from the Autonomous Community of Galicia within the framework of the Biotechnology Plan Applied to Health.

r-somnmr 0.3.0
Propagated dependencies: r-rlang@1.1.6 r-quadprog@1.5-8 r-pracma@2.4.6 r-minpack-lm@1.2-4 r-intervalsurgeon@1.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/LuisCol8/SOMnmR/
Licenses: Expat
Build system: r
Synopsis: Analysis of Soil Organic Matter using Nuclear Magnetic Resonance
Description:

Integrates the 13C nuclear magnetic resonance spectra using different integration ranges. Output depends on the method chosen. For the Molecular Mixing Model, a measurement of the fitting quality is given by its R-factor. For more details see: <doi:10.5281/zenodo.10137768>.

r-steppedpower 0.3.5
Propagated dependencies: r-rfast@2.1.5.2 r-plotly@4.11.0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SteppedPower
Licenses: Expat
Build system: r
Synopsis: Power Calculation for Stepped Wedge Designs
Description:

This package provides tools for power and sample size calculation as well as design diagnostics for longitudinal mixed model settings, with a focus on stepped wedge designs. All calculations are oracle estimates i.e. assume random effect variances to be known (or guessed) in advance. The method is introduced in Hussey and Hughes (2007) <doi:10.1016/j.cct.2006.05.007>, extensions are discussed in Li et al. (2020) <doi:10.1177/0962280220932962>.

r-slurmr 0.5-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/USCbiostats/slurmR
Licenses: Expat
Build system: r
Synopsis: Lightweight Wrapper for 'Slurm'
Description:

Slurm', Simple Linux Utility for Resource Management <https://slurm.schedmd.com/>, is a popular Linux based software used to schedule jobs in HPC (High Performance Computing) clusters. This R package provides a specialized lightweight wrapper of Slurm with a syntax similar to that found in the parallel R package. The package also includes a method for creating socket cluster objects spanning multiple nodes that can be used with the parallel package.

r-shinyratings 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-jsonlite@2.0.0 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shinyRatings
Licenses: Expat
Build system: r
Synopsis: An Intuitive Way of Providing Star Rating in a 'shiny' App
Description:

This package provides a simple interface to integrate star ratings into your shiny apps. It can be used for customer feedback systems, user reviews, or any application that requires user ratings. shinyRatings offers a straightforward and customisable solution that enhances user engagement and facilitates valuable feedback collection.

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+
Build system: r
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-staninside 0.0.4
Propagated dependencies: r-rappdirs@0.3.3 r-fs@1.6.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/medewitt/staninside
Licenses: Expat
Build system: r
Synopsis: Facilitating the Use of 'Stan' Within Packages
Description:

Infrastructure and functions that can be used for integrating Stan (Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>) code into stand alone R packages which in turn use the CmdStan engine which is often accessed through CmdStanR'. Details given in Stan Development Team (2025) <https://mc-stan.org/cmdstanr/>. Using CmdStanR and pre-written Stan code can make package installation easy. Using staninside offers a way to cache user-compiled Stan models in user-specified directories reducing the need to recompile the same model multiple times.

r-stpp 2.0-8
Propagated dependencies: r-splancs@2.01-45 r-spatstat-univar@3.1-5 r-spatstat-random@3.4-3 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-rpanel@1.1-5.2 r-rgl@1.3.31 r-plot3d@1.4.2 r-kernsmooth@2.23-26 r-gridextra@2.3 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=stpp
Licenses: GPL 3
Build system: r
Synopsis: Space-Time Point Pattern Simulation, Visualisation and Analysis
Description:

Many of the models encountered in applications of point process methods to the study of spatio-temporal phenomena are covered in stpp'. This package provides statistical tools for analyzing the global and local second-order properties of spatio-temporal point processes, including estimators of the space-time inhomogeneous K-function and pair correlation function. It also includes tools to get static and dynamic display of spatio-temporal point patterns. See Gabriel et al (2013) <doi:10.18637/jss.v053.i02>.

r-scbmeanfd 1.2.3
Propagated dependencies: r-kernsmooth@2.23-26 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://CRAN.R-project.org/package=SCBmeanfd
Licenses: GPL 3
Build system: r
Synopsis: Simultaneous Confidence Bands for the Mean of Functional Data
Description:

Statistical methods for estimating and inferring the mean of functional data. The methods include simultaneous confidence bands, local polynomial fitting, bandwidth selection by plug-in and cross-validation, goodness-of-fit tests for parametric models, equality tests for two-sample problems, and plotting functions.

r-sas7bdat 0.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sas7bdat
Licenses: GPL 2+
Build system: r
Synopsis: sas7bdat Reverse Engineering Documentation
Description:

Documentation and prototypes for the earliest (circa 2010) open-source effort to reverse engineer the sas7bdat file format. The package includes a prototype reader for sas7bdat files. However, newer packages may contain more robust readers for sas7bdat files.

r-scisr 0.1.1
Propagated dependencies: r-pinsplus@2.0.9 r-matrixstats@1.5.0 r-markdown@2.0 r-irlba@2.3.5.1 r-entropy@1.3.2 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/duct317/scISR
Licenses: LGPL 2.0+
Build system: r
Synopsis: Single-Cell Imputation using Subspace Regression
Description:

This package provides an imputation pipeline for single-cell RNA sequencing data. The scISR method uses a hypothesis-testing technique to identify zero-valued entries that are most likely affected by dropout events and estimates the dropout values using a subspace regression model (Tran et.al. (2022) <DOI:10.1038/s41598-022-06500-4>).

r-simplefdr 1.1
Propagated dependencies: r-tidyr@1.3.1 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=simpleFDR
Licenses: Expat
Build system: r
Synopsis: Simple False Discovery Rate Calculation
Description:

Using the adjustment method from Benjamini & Hochberg (1995) <doi:10.1111/j.2517-6161.1995.tb02031.x>, this package determines which variables are significant under repeated testing with a given dataframe of p values and an user defined "q" threshold. It then returns the original dataframe along with a significance column where an asterisk denotes a significant p value after FDR calculation, and NA denotes all other p values. This package uses the Benjamini & Hochberg method specifically as described in Lee, S., & Lee, D. K. (2018) <doi:10.4097/kja.d.18.00242>.

r-solitude 1.1.3
Propagated dependencies: r-ranger@0.17.0 r-r6@2.6.1 r-lgr@0.5.0 r-igraph@2.2.1 r-future-apply@1.20.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/talegari/solitude
Licenses: GPL 3
Build system: r
Synopsis: An Implementation of Isolation Forest
Description:

Isolation forest is anomaly detection method introduced by the paper Isolation based Anomaly Detection (Liu, Ting and Zhou <doi:10.1145/2133360.2133363>).

r-smcfcs 2.0.1
Propagated dependencies: r-vgam@1.1-13 r-survival@3.8-3 r-rlang@1.1.6 r-mass@7.3-65 r-checkmate@2.3.3 r-brglm2@1.0.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jwb133/smcfcs
Licenses: GPL 3
Build system: r
Synopsis: Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Description:

This package implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.

r-stylo 0.7.5
Propagated dependencies: r-tsne@0.1-3.1 r-tcltk2@1.6.1 r-pamr@1.57 r-lattice@0.22-7 r-e1071@1.7-16 r-class@7.3-23 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/computationalstylistics/stylo
Licenses: GPL 3+
Build system: r
Synopsis: Stylometric Multivariate Analyses
Description:

Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.

r-stfts 0.1.0
Propagated dependencies: r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=STFTS
Licenses: GPL 2
Build system: r
Synopsis: Statistical Tests for Functional Time Series
Description:

This package provides a collection of statistical hypothesis tests of functional time series. While it will include more tests when the related literature are enriched, this package contains the following key tests: functional stationarity test, functional trend stationarity test, functional unit root test, to name a few.

r-selenium 0.2.0
Propagated dependencies: r-rlang@1.1.6 r-rappdirs@0.3.3 r-r6@2.6.1 r-processx@3.8.6 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr2@1.2.1 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://ashbythorpe.github.io/selenium-r/
Licenses: Expat
Build system: r
Synopsis: Low-Level Browser Automation Interface
Description:

An implementation of W3C WebDriver 2.0 (<https://w3c.github.io/webdriver/>), allowing interaction with a Selenium Server (<https://www.selenium.dev/documentation/grid/>) instance from R'. Allows a web browser to be automated from R'.

r-shattering 1.0.7
Propagated dependencies: r-slam@0.1-55 r-ryacas@1.1.6 r-rmarkdown@2.30 r-pracma@2.4.6 r-pdist@1.2.1 r-nmf@0.28 r-fnn@1.1.4.1 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shattering
Licenses: GPL 3
Build system: r
Synopsis: Estimate the Shattering Coefficient for a Particular Dataset
Description:

The Statistical Learning Theory (SLT) provides the theoretical background to ensure that a supervised algorithm generalizes the mapping f:X -> Y given f is selected from its search space bias F. This formal result depends on the Shattering coefficient function N(F,2n) to upper bound the empirical risk minimization principle, from which one can estimate the necessary training sample size to ensure the probabilistic learning convergence and, most importantly, the characterization of the capacity of F, including its under and overfitting abilities while addressing specific target problems. In this context, we propose a new approach to estimate the maximal number of hyperplanes required to shatter a given sample, i.e., to separate every pair of points from one another, based on the recent contributions by Har-Peled and Jones in the dataset partitioning scenario, and use such foundation to analytically compute the Shattering coefficient function for both binary and multi-class problems. As main contributions, one can use our approach to study the complexity of the search space bias F, estimate training sample sizes, and parametrize the number of hyperplanes a learning algorithm needs to address some supervised task, what is specially appealing to deep neural networks. Reference: de Mello, R.F. (2019) "On the Shattering Coefficient of Supervised Learning Algorithms" <arXiv:1911.05461>; de Mello, R.F., Ponti, M.A. (2018, ISBN: 978-3319949888) "Machine Learning: A Practical Approach on the Statistical Learning Theory".

r-smvgraph 0.1.2
Propagated dependencies: r-sortable@0.6.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-mass@7.3-65 r-fmsb@0.7.6 r-desctools@0.99.60
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=smvgraph
Licenses: GPL 3
Build system: r
Synopsis: Various Multivariate Graphics with Variable Choice in Shiny Apps
Description:

Mosaic diagram, scatterplot matrix, Andrews curves, parallel coordinate diagram, radar diagram, and Chernoff plots as a Shiny app, which allow the order of variables to be changed interactively. The apps are intended as teaching examples.

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