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

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-futurize 0.1.0
Propagated dependencies: r-future@1.68.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://www.futureverse.org
Licenses: GPL 3+
Build system: r
Synopsis: Parallelize Common Functions via One Magic Function
Description:

The futurize() function transpiles calls to sequential map-reduce functions such as base::lapply(), purrr::map(), foreach::foreach() %do% ... into concurrent alternatives, providing you with a simple, straightforward path to scalable parallel computing via the future ecosystem <doi:10.32614/RJ-2021-048>. By combining this function with R's native pipe operator, you have an convenient way for speeding up iterative computations with minimal refactoring, e.g. lapply(xs, fcn) |> futurize()', purrr::map(xs, fcn) |> futurize()', and foreach::foreach(x = xs) %do% fcn(x) |> futurize()'. Other map-reduce packages that be "futurized" are BiocParallel', plyr', crossmap packages. There is also support for growing set of domain-specific packages, including boot', glmnet', mgcv', lme4', and tm'.

r-featureterminator 1.0.0
Propagated dependencies: r-tibble@3.3.0 r-randomforest@4.7-1.2 r-lattice@0.22-7 r-ggplot2@4.0.1 r-e1071@1.7-16 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FeatureTerminatoR
Licenses: GPL 3
Build system: r
Synopsis: Feature Selection Engine to Remove Features with Minimal Predictive Power
Description:

The aim is to take in data.frame inputs and utilises methods, such as recursive feature engineering, to enable the features to be removed. What this does differently from the other packages, is that it gives you the choice to remove the variables manually, or it automated this process. Feature selection is a concept in machine learning, and statistical pipelines, whereby unimportant, or less predictive variables are eliminated from the analysis, see Boughaci (2018) <doi:10.1007/s40595-018-0107-y>.

r-future-batchtools 0.21.0
Propagated dependencies: r-stringi@1.8.7 r-parallelly@1.45.1 r-future@1.68.0 r-checkmate@2.3.3 r-batchtools@0.9.18
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://future.batchtools.futureverse.org
Licenses: LGPL 2.1+
Build system: r
Synopsis: Future API for Parallel and Distributed Processing using 'batchtools'
Description:

Implementation of the Future API <doi:10.32614/RJ-2021-048> on top of the batchtools package. This allows you to process futures, as defined by the future package, in parallel out of the box, not only on your local machine or ad-hoc cluster of machines, but also via high-performance compute ('HPC') job schedulers such as LSF', OpenLava', Slurm', SGE', and TORQUE / PBS', e.g. y <- future.apply::future_lapply(files, FUN = process)'.

r-filebin 0.0.6
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringi@1.8.7 r-purrr@1.2.0 r-logger@0.4.1 r-janitor@2.2.1 r-httr@1.4.7 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=filebin
Licenses: GPL 3
Build system: r
Synopsis: Wrapper for the Filebin File Sharing API
Description:

This package provides a wrapper for the Filebin API. Filebin implements convenient file sharing on the web.

r-facilityepimath 0.2.1
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/EpiForeSITE/facilityepimath
Licenses: Expat
Build system: r
Synopsis: Analyze Mathematical Models of Healthcare Facility Transmission
Description:

Calculate useful quantities for a user-defined differential equation model of infectious disease transmission among individuals in a healthcare facility. Input rates of transition between states of individuals with and without the disease-causing organism, distributions of states at facility admission, relative infectivity of transmissible states, and the facility length of stay distribution. Calculate the model equilibrium and the basic facility reproduction number, as described in Toth et al. (2025) <doi:10.1371/journal.pcbi.1013577>.

r-floral 0.6.0
Propagated dependencies: r-survival@3.8-3 r-survcomp@1.60.0 r-reshape@0.8.10 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-phyloseq@1.54.0 r-mvtnorm@1.3-3 r-msm@1.8.2 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-dorng@1.8.6.2 r-doparallel@1.0.17 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://vdblab.github.io/FLORAL/
Licenses: GPL 3+
Build system: r
Synopsis: Fit Log-Ratio Lasso Regression for Compositional Data
Description:

Log-ratio Lasso regression for continuous, binary, and survival outcomes with (longitudinal) compositional features. See Fei and others (2024) <doi:10.1016/j.crmeth.2024.100899>.

r-frheritage 0.1.0
Propagated dependencies: r-xml2@1.5.0 r-sf@1.0-23 r-jsonlite@2.0.0 r-httr2@1.2.1 r-happign@0.3.7
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=frheritage
Licenses: GPL 3+
Build system: r
Synopsis: R Interface to Get French Heritage Data
Description:

Get spatial vector data from the Atlas du Patrimoine (<http://atlas.patrimoines.culture.fr/atlas/trunk/>), the official national platform of the French Ministry of Culture, and facilitate its use within R geospatial workflows. The package provides functions to list available heritage datasets, query and retrieve heritage data using spatial queries based on user-provided sf objects, perform spatial filtering operations, and return results as sf objects suitable for spatial analysis, mapping, and integration into heritage management and landscape studies.

r-ftextra 0.6.4
Propagated dependencies: r-yaml@2.3.10 r-xfun@0.54 r-vctrs@0.6.5 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rmarkdown@2.30 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-flextable@0.9.10 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://ftextra.atusy.net
Licenses: Expat
Build system: r
Synopsis: Extensions for 'Flextable'
Description:

Build display tables easily by extending the functionality of the flextable package. Features include spanning header, grouping rows, parsing markdown and so on.

r-fermicatsr 1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/sazpark/fermicatsR.git
Licenses: CC0
Build system: r
Synopsis: Fermi Large Area Telescope Catalogs
Description:

Data from various catalogs of astrophysical gamma-ray sources detected by NASA's Large Area Telescope (The Astrophysical Journal, 697, 1071, 2009 June 1), on board the Fermi gamma-ray satellite. More information on Fermi and its data products is available from the Fermi Science Support Center (http://fermi.gsfc.nasa.gov/ssc/).

r-fitzroy 1.6.0
Propagated dependencies: r-xml2@1.5.0 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rvest@1.0.5 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-janitor@2.2.1 r-httr2@1.2.1 r-httr@1.4.7 r-glue@1.8.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://jimmyday12.github.io/fitzRoy/
Licenses: Expat
Build system: r
Synopsis: Easily Scrape and Process AFL Data
Description:

An easy package for scraping and processing Australia Rules Football (AFL) data. fitzRoy provides a range of functions for accessing publicly available data from AFL Tables <https://afltables.com/afl/afl_index.html>, Footy Wire <https://www.footywire.com> and The Squiggle <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.

r-faoutlier 0.7.7
Propagated dependencies: r-sem@3.1-16 r-pbapply@1.7-4 r-mvtnorm@1.3-3 r-mirt@1.45.1 r-mass@7.3-65 r-lavaan@0.6-20 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/philchalmers/faoutlier
Licenses: GPL 2+
Build system: r
Synopsis: Influential Case Detection Methods for Factor Analysis and Structural Equation Models
Description:

This package provides tools for detecting and summarize influential cases that can affect exploratory and confirmatory factor analysis models as well as structural equation models more generally (Chalmers, 2015, <doi:10.1177/0146621615597894>; Flora, D. B., LaBrish, C. & Chalmers, R. P., 2012, <doi:10.3389/fpsyg.2012.00055>).

r-fuzzypovertyr 3.0.2
Propagated dependencies: r-tidyr@1.3.1 r-sampling@2.11 r-ggplot2@4.0.1 r-ecp@3.1.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FuzzyPovertyR
Licenses: Expat
Build system: r
Synopsis: Estimation of Fuzzy Poverty Measures
Description:

Estimates fuzzy measures of poverty and deprivation. It also estimates the sampling variance of these measures using bootstrap or jackknife repeated replications.

r-fkml 0.1.1
Propagated dependencies: r-proxy@0.4-27 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FKmL
Licenses: GPL 2+
Build system: r
Synopsis: Fréchet Distance-Based K-Means and Extensions for Longitudinal Data
Description:

This package implements shape-based clustering algorithms for multidimensional longitudinal data based on the Fréchet distance. It implements two main methods: MFKmL (Multidimensional Fréchet distance-based K-means for Longitudinal data), an extension of the K-means algorithm using the Fréchet distance originally developed in the kmlShape package, adapted for multidimensional trajectories; and SFKmL (Sparse multidimensional Fréchet distance-based K-medoids for Longitudinal data), a K-medoids-based clustering algorithm that incorporates variable selection. These tools are designed to enhance clustering performance in high-dimensional longitudinal data settings, particularly those with time delays, variations in trajectory speed, irregular sampling intervals, and noise. This package implements methods derived from Kang et al. (2023) <doi:10.1007/s11222-023-10237-z>.

r-findsvi 0.2.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tidycensus@1.7.3 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/heli-xu/findSVI
Licenses: Expat
Build system: r
Synopsis: Calculate Social Vulnerability Index for Communities
Description:

Developed by CDC/ATSDR (Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry), Social Vulnerability Index (SVI) serves as a tool to assess the resilience of communities by taking into account socioeconomic and demographic factors. Provided with year(s), region(s) and a geographic level of interest, findSVI retrieves required variables from US census data and calculates SVI for communities in the specified area based on CDC/ATSDR SVI documentation. Reference for the calculation methods: Flanagan BE, Gregory EW, Hallisey EJ, Heitgerd JL, Lewis B (2011) <doi:10.2202/1547-7355.1792>.

r-faq 0.1.1
Propagated dependencies: r-jsonlite@2.0.0 r-htmlwidgets@1.6.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=faq
Licenses: Expat
Build system: r
Synopsis: Create FAQ Page
Description:

Create Frequently Asked Questions page for Shiny application.

r-fattailsr 2.0.0
Propagated dependencies: r-timeseries@4041.111 r-minpack-lm@1.2-4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://www.inmodelia.com/fattailsr-en.html
Licenses: GPL 2
Build system: r
Synopsis: Kiener Distributions and Fat Tails in Finance and Neuroscience
Description:

Kiener distributions K1, K2, K3, K4 and K7 to characterize distributions with left and right, symmetric or asymmetric fat tails in finance, neuroscience and other disciplines. Two algorithms to estimate the distribution parameters, quantiles, value-at-risk and expected shortfall. IMPORTANT: Standardization has been changed in versions >= 2.0.0 to get sd = 1 when kappa = Inf rather than 2*pi/sqrt(3) in versions <= 1.8.6. This affects parameter g (other parameters stay unchanged). Do not update if you need consistent comparisons with previous results for the g parameter.

r-fpass 1.0.0
Propagated dependencies: r-testthat@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-nlme@3.1-168 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-gss@2.2-10 r-gamm4@0.2-7 r-face@0.1-8 r-expm@1.0-0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/SalilKoner/fPASS
Licenses: Expat
Build system: r
Synopsis: Power and Sample Size for Projection Test under Repeated Measures
Description:

Computes the power and sample size (PASS) required to test for the difference in the mean function between two groups under a repeatedly measured longitudinal or sparse functional design. See the manuscript by Koner and Luo (2023) <https://salilkoner.github.io/assets/PASS_manuscript.pdf> for details of the PASS formula and computational details. The details of the testing procedure for univariate and multivariate response are presented in Wang (2021) <doi:10.1214/21-EJS1802> and Koner and Luo (2023) <arXiv:2302.05612> respectively.

r-flexlsx 0.3.5
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringi@1.8.7 r-rlang@1.1.6 r-rcpp@1.1.0 r-purrr@1.2.0 r-openxlsx2@1.23.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/pteridin/flexlsx
Licenses: Expat
Build system: r
Synopsis: Exporting 'flextable' to 'xlsx' Files
Description:

Exports flextable objects to xlsx files, utilizing functionalities provided by flextable and openxlsx2'.

r-features 2025.1
Propagated dependencies: r-lokern@1.1-12
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=features
Licenses: GPL 2+
Build system: r
Synopsis: Feature Extraction for Discretely-Sampled Functional Data
Description:

Discretely-sampled function is first smoothed. Features of the smoothed function are then extracted. Some of the key features include mean value, first and second derivatives, critical points (i.e. local maxima and minima), curvature of cunction at critical points, wiggliness of the function, noise in data, and outliers in data.

r-fastgasp 0.6.2
Propagated dependencies: r-rstiefel@1.0.1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FastGaSP
Licenses: GPL 2+
Build system: r
Synopsis: Fast and Exact Computation of Gaussian Stochastic Process
Description:

This package implements fast and exact computation of Gaussian stochastic process with the Matern kernel using forward filtering and backward smoothing algorithm. It includes efficient implementations of the inverse Kalman filter, with applications such as estimating particle interaction functions. These tools support models with or without noise. Additionally, the package offers algorithms for fast parameter estimation in latent factor models, where the factor loading matrix is orthogonal, and latent processes are modeled by Gaussian processes. See the references: 1) Mengyang Gu and Yanxun Xu (2020), Journal of Computational and Graphical Statistics; 2) Xinyi Fang and Mengyang Gu (2024), <doi:10.48550/arXiv.2407.10089>; 3) Mengyang Gu and Weining Shen (2020), Journal of Machine Learning Research; 4) Yizi Lin, Xubo Liu, Paul Segall and Mengyang Gu (2025), <doi:10.48550/arXiv.2501.01324>.

r-fitplotr 0.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fitPlotR
Licenses: GPL 3
Build system: r
Synopsis: Plotting Probability Distributions
Description:

This package provides functions for plotting probability density functions, distribution functions, survival functions, hazard functions and computing distribution moments. The implementation is inspired by Delignette-Muller and Dutang (2015) <doi:10.18637/jss.v064.i04>.

r-fluxpoint 0.1.2
Propagated dependencies: r-simdesign@2.21 r-pracma@2.4.6 r-nnls@1.6 r-matrix@1.7-4 r-mass@7.3-65 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-doparallel@1.0.17 r-corpcor@1.6.10 r-blockmatrix@1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FluxPoint
Licenses: GPL 2
Build system: r
Synopsis: Change Point Detection for Non-Stationary and Cross-Correlated Time Series
Description:

This package implements methods for multiple change point detection in multivariate time series with non-stationary dynamics and cross-correlations. The methodology is based on a model in which each component has a fluctuating mean represented by a random walk with occasional abrupt shifts, combined with a stationary vector autoregressive structure to capture temporal and cross-sectional dependence. The framework is broadly applicable to correlated multivariate sequences in which large, sudden shifts occur in all or subsets of components and are the primary targets of interest, whereas small, smooth fluctuations are not. Although random walks are used as a modeling device, they provide a flexible approximation for a wide class of slowly varying or locally smooth dynamics, enabling robust performance beyond the strict random walk setting.

r-fucom 0.0.4
Propagated dependencies: r-nloptr@2.2.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fucom
Licenses: GPL 3+
Build system: r
Synopsis: Full Consistency Method (FUCOM)
Description:

Full Consistency Method (FUCOM) for multi-criteria decision-making (MCDM), developed by Dragam Pamucar in 2018 (<doi:10.3390/sym10090393>). The goal of the method is to determine the weights of criteria such that the deviation from full consistency is minimized. Users provide a character vector specifying the ranking of each criterion according to its significance, starting from the criterion expected to have the highest weight to the least significant one. Additionally, users provide a numeric vector specifying the priority values for each criterion. The comparison is made with respect to the first-ranked (most significant) criterion. The function returns the optimized weights for each criterion (summing to 1), the comparative priority (Phi) values, the mathematical transitivity condition (w) value, and the minimum deviation from full consistency (DFC).

r-fgeo-analyze 1.1.15
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-mass@7.3-65 r-magrittr@2.0.4 r-lubridate@1.9.4 r-glue@1.8.0 r-fgeo-tool@1.2.10 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/forestgeo/fgeo.analyze
Licenses: GPL 3
Build system: r
Synopsis: Analyze ForestGEO Data
Description:

To help you access, transform, analyze, and visualize ForestGEO data, we developed a collection of R packages (<https://forestgeo.github.io/fgeo/>). This package, in particular, helps you to implement analyses of plot species distributions, topography, demography, and biomass. It also includes a torus translation test to determine habitat associations of tree species as described by Zuleta et al. (2018) <doi:10.1007/s11104-018-3878-0>. To learn more about ForestGEO visit <https://forestgeo.si.edu/>.

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