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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-fiesta 3.7.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://usdaforestservice.github.io/FIESTA/
Licenses: GPL 3
Build system: r
Synopsis: Forest Inventory Estimation and Analysis
Description:

This package provides a research estimation tool for analysts that work with sample-based inventory data from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program.

r-fasterraster 8.4.1.1
Dependencies: grass@8.4.1
Propagated dependencies: r-terra@1.8-86 r-shiny@1.11.1 r-sf@1.0-23 r-rgrass@0.5-3 r-omnibus@1.2.15 r-dt@0.34.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/adamlilith/fasterRaster
Licenses: GPL 3+
Build system: r
Synopsis: Faster Raster and Spatial Vector Processing Using 'GRASS'
Description:

Processing of large-in-memory/large-on disk rasters and spatial vectors using GRASS <https://grass.osgeo.org/>. Most functions in the terra package are recreated. Processing of medium-sized and smaller spatial objects will nearly always be faster using terra or sf', but for large-in-memory/large-on-disk objects, fasterRaster may be faster. To use most of the functions, you must have the stand-alone version (not the OSGeoW4 installer version) of GRASS 8.0 or higher.

r-fable-ata 0.0.6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://alsabtay.github.io/fable.ata/
Licenses: GPL 3+
Build system: r
Synopsis: 'ATAforecasting' Modelling Interface for 'fable' Framework
Description:

Allows ATA (Automatic Time series analysis using the Ata method) models from the ATAforecasting package to be used in a tidy workflow with the modeling interface of fabletools'. This extends ATAforecasting to provide enhanced model specification and management, performance evaluation methods, and model combination tools. The Ata method (Yapar et al. (2019) <doi:10.15672/hujms.461032>), an alternative to exponential smoothing (described in Yapar (2016) <doi:10.15672/HJMS.201614320580>, Yapar et al. (2017) <doi:10.15672/HJMS.2017.493>), is a new univariate time series forecasting method which provides innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods. Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal).

r-frcc 1.1.0
Propagated dependencies: r-mass@7.3-65 r-corpcor@1.6.10 r-ccp@1.2 r-calibrate@1.7.7
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FRCC
Licenses: GPL 2+
Build system: r
Synopsis: Fast Regularized Canonical Correlation Analysis
Description:

This package contains the core functions associated with Fast Regularized Canonical Correlation Analysis. Please see the following for details: Raul Cruz-Cano, Mei-Ling Ting Lee, Fast regularized canonical correlation analysis, Computational Statistics & Data Analysis, Volume 70, 2014, Pages 88-100, ISSN 0167-9473 <doi:10.1016/j.csda.2013.09.020>.

r-funitroots 4052.82
Propagated dependencies: r-urca@1.3-4 r-timeseries@4041.111 r-fbasics@4041.97
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://geobosh.github.io/fUnitRootsDoc/
Licenses: GPL 2+
Build system: r
Synopsis: Rmetrics - Modelling Trends and Unit Roots
Description:

This package provides four addons for analyzing trends and unit roots in financial time series: (i) functions for the density and probability of the augmented Dickey-Fuller Test, (ii) functions for the density and probability of MacKinnon's unit root test statistics, (iii) reimplementations for the ADF and MacKinnon Test, and (iv) an urca Unit Root Test Interface for Pfaff's unit root test suite.

r-fbn 1.5.2
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FBN
Licenses: GPL 2+
Build system: r
Synopsis: FISH Based Normalization and Copy Number Inference of SNP Microarray Data
Description:

Normalizes the data from a file containing the raw values of the SNP probes of microarray data by using the FISH probes and their corresponding copy number.

r-fedirt 1.1.0
Propagated dependencies: r-shinyjs@2.1.0 r-shiny@1.11.1 r-purrr@1.2.0 r-pracma@2.4.6 r-httr@1.4.7 r-ggplot2@4.0.1 r-dt@0.34.0 r-callr@3.7.6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FedIRT
Licenses: Expat
Build system: r
Synopsis: Federated Item Response Theory Models
Description:

Integrate Item Response Theory (IRT) and Federated Learning to estimate traditional IRT models, including the 2-Parameter Logistic (2PL) and the Graded Response Models, with enhanced privacy. It allows for the estimation in a distributed manner without compromising accuracy. A user-friendly shiny application is included.

r-fuzzynumbers 0.4-7
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/gagolews/FuzzyNumbers/
Licenses: LGPL 3+
Build system: r
Synopsis: Tools to Deal with Fuzzy Numbers
Description:

S4 classes and methods to deal with fuzzy numbers. They allow for computing any arithmetic operations (e.g., by using the Zadeh extension principle), performing approximation of arbitrary fuzzy numbers by trapezoidal and piecewise linear ones, preparing plots for publications, computing possibility and necessity values for comparisons, etc.

r-firestorm 0.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/thomasp85/firestorm
Licenses: Expat
Build system: r
Synopsis: Reverse Proxy and Load Balancing for 'fiery'
Description:

This package provides plugins for setting up fiery apps as a reverse proxy. This allows you to use a fiery server as a front for multiple services or even work as a load-balancer.

r-fitultd 3.1.0
Propagated dependencies: r-purrr@1.2.0 r-mclust@6.1.2 r-mass@7.3-65 r-ggplot2@4.0.1 r-fitdistrplus@1.2-4 r-cowplot@1.2.0 r-assertthat@0.2.1 r-adgoftest@0.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/jcval94/FitUltD
Licenses: GPL 3
Build system: r
Synopsis: Fit Univariate Mixed and Usual Distributions
Description:

Extends the fitdist() (from fitdistrplus') adding the Anderson-Darling ad.test() (from ADGofTest') and Kolmogorov Smirnov Test ks.test() inside, trying the distributions from stats package by default and offering a second function which uses mixed distributions to fit, this distributions are split with unsupervised learning, with Mclust() function (from mclust').

r-flexbart 2.0.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://skdeshpande91.github.io/flexBART/
Licenses: GPL 3+
Build system: r
Synopsis: More Flexible BART Model
Description:

This package implements a faster and more expressive version of Bayesian Additive Regression Trees that, at a high level, approximates unknown functions as a weighted sum of binary regression tree ensembles. Supports fitting (generalized) linear varying coefficient models that posits a linear relationship between the inverse link and some covariates but allows that relationship to change as a function of other covariates. Additionally supports fitting heteroscedastic BART models, in which both the mean and log-variance are approximated with separate regression tree ensembles. A formula interface allows for different splitting variables to be used in each ensemble. For more details see Deshpande (2025) <doi:10.1080/10618600.2024.2431072> and Deshpande et al. (2024) <doi:10.1214/24-BA1470>.

r-fmriscrub 0.14.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/mandymejia/fMRIscrub
Licenses: GPL 3
Build system: r
Synopsis: Scrubbing and Other Data Cleaning Routines for fMRI
Description:

Data-driven fMRI denoising with projection scrubbing (Pham et al (2022) <doi:10.1016/j.neuroimage.2023.119972>). Also includes routines for DVARS (Derivatives VARianceS) (Afyouni and Nichols (2018) <doi:10.1016/j.neuroimage.2017.12.098>), motion scrubbing (Power et al (2012) <doi:10.1016/j.neuroimage.2011.10.018>), aCompCor (anatomical Components Correction) (Muschelli et al (2014) <doi:10.1016/j.neuroimage.2014.03.028>), detrending, and nuisance regression. Projection scrubbing is also applicable to other outlier detection tasks involving high-dimensional data.

r-finalsize 0.2.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/epiverse-trace/finalsize
Licenses: Expat
Build system: r
Synopsis: Calculate the Final Size of an Epidemic
Description:

Calculate the final size of a susceptible-infectious-recovered epidemic in a population with demographic variation in contact patterns and susceptibility to disease, as discussed in Miller (2012) <doi:10.1007/s11538-012-9749-6>.

r-frf2 2.3-4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://prof.bht-berlin.de/groemping/DoE/
Licenses: GPL 2+
Build system: r
Synopsis: Fractional Factorial Designs with 2-Level Factors
Description:

Regular and non-regular Fractional Factorial 2-level designs can be created. Furthermore, analysis tools for Fractional Factorial designs with 2-level factors are offered (main effects and interaction plots for all factors simultaneously, cube plot for looking at the simultaneous effects of three factors, full or half normal plot, alias structure in a more readable format than with the built-in function alias).

r-fastfmm 1.0.0
Propagated dependencies: r-stringr@1.6.0 r-rfast@2.1.5.2 r-refund@0.1-38 r-progress@1.2.3 r-mvtnorm@1.3-3 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-lsei@1.3-0 r-lmeresampler@0.2.4 r-lme4@1.1-37 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-caic4@1.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/gloewing/fastFMM
Licenses: GPL 3+
Build system: r
Synopsis: Fast Functional Mixed Models using Fast Univariate Inference
Description:

Implementation of the fast univariate inference approach (Cui et al. (2022) <doi:10.1080/10618600.2021.1950006>, Loewinger et al. (2024) <doi:10.7554/eLife.95802.2>, Xin et al. (2025)) for fitting functional mixed models. User guides and Python package information can be found at <https://github.com/gloewing/photometry_FLMM>.

r-formulr 1.0.0
Propagated dependencies: r-knitr@1.50 r-ggplot2@4.0.1 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=FormulR
Licenses: Expat
Build system: r
Synopsis: Comprehensive Tools for Drug Formulation Analysis and Visualization
Description:

This presents a comprehensive set of tools for the analysis and visualization of drug formulation data. It includes functions for statistical analysis, regression modeling, hypothesis testing, and comparative analysis to assess the impact of formulation parameters on drug release and other critical attributes. Additionally, the package offers a variety of data visualization functions, such as scatterplots, histograms, and boxplots, to facilitate the interpretation of formulation data. With its focus on usability and efficiency, this package aims to streamline the drug formulation process and aid researchers in making informed decisions during formulation design and optimization.

r-fcl 0.1.4
Propagated dependencies: r-ymd@0.1.5 r-xts@0.14.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/shrektan/fcl
Licenses: Expat
Build system: r
Synopsis: Financial Calculator
Description:

This package provides a financial calculator that provides very fast implementations of common financial indicators using Rust code. It includes functions for bond-related indicators, such as yield to maturity ('YTM'), modified duration, and Macaulay duration, as well as functions for calculating time-weighted and money-weighted rates of return (using Modified Dietz method) for multiple portfolios, given their market values and profit and loss ('PnL') data. fcl is designed to be efficient and accurate for financial analysis and computation. The methods used in this package are based on the following references: <https://en.wikipedia.org/wiki/Modified_Dietz_method>, <https://en.wikipedia.org/wiki/Time-weighted_return>.

r-fuzzyforest 1.0.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fuzzyforest
Licenses: GPL 3
Build system: r
Synopsis: Fuzzy Forests
Description:

Fuzzy forests, a new algorithm based on random forests, is designed to reduce the bias seen in random forest feature selection caused by the presence of correlated features. Fuzzy forests uses recursive feature elimination random forests to select features from separate blocks of correlated features where the correlation within each block of features is high and the correlation between blocks of features is low. One final random forest is fit using the surviving features. This package fits random forests using the randomForest package and allows for easy use of WGCNA to split features into distinct blocks. See D. Conn, Ngun, T., C. Ramirez, and G. Li (2019) <doi:10.18637/jss.v091.i09> for further details.

r-fusedtree 1.1.0
Propagated dependencies: r-treeclust@1.1-7.1 r-survival@3.8-3 r-splittools@1.0.1 r-partykit@1.2-24 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fusedTree
Licenses: GPL 3+
Build system: r
Synopsis: Fused Partitioned Regression for Clinical and Omics Data
Description:

Fit (generalized) linear regression models in each leaf node of a tree. The tree is constructed using clinical variables only. The linear regression models are constructed using (high-dimensional) omics variables only. The leaf-node-specific regression models are estimated using the penalized likelihood including a standard ridge (L2) penalty and a fusion penalty that links the leaf-node-specific regression models to one another. The intercepts of the leaf nodes reflect the effects of the clinical variables and are left unpenalized. The tree, fitted with the clinical variables only, should be constructed outside of the package with the rpart R package. See Goedhart and others (2024) <doi:10.48550/arXiv.2411.02396> for details on the method.

r-fingerpro 2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/eead-csic-eesa/fingerPro
Licenses: GPL 3+
Build system: r
Synopsis: Comprehensive Package for Sediment Source Unmixing
Description:

"This package quantifies the provenance of sediments in a catchment or study area. Based on a characterization of the sediment sources and the end sediment mixtures, a mixing model algorithm is applied to the sediment mixtures to estimate the relative contribution of each potential source. The package includes several graphs to help users in their data understanding, such as box plots, correlation, PCA, and LDA graphs. In addition, new developments such as the Consensus Ranking (CR), Consistent Tracer Selection (CTS), and Linear Variability Propagation (LVP) methods are included to correctly apply the fingerprinting technique and increase dataset and model understanding. A new method based on Conservative Balance (CB) method has also been included to enable the use of isotopic tracers.".

r-fdasrvf 2.4.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/jdtuck/fdasrvf_R
Licenses: GPL 3
Build system: r
Synopsis: Elastic Functional Data Analysis
Description:

This package performs alignment, PCA, and modeling of multidimensional and unidimensional functions using the square-root velocity framework (Srivastava et al., 2011 <doi:10.48550/arXiv.1103.3817> and Tucker et al., 2014 <DOI:10.1016/j.csda.2012.12.001>). This framework allows for elastic analysis of functional data through phase and amplitude separation.

r-fixr 0.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/ambuvjyn/fixr
Licenses: GPL 3
Build system: r
Synopsis: Fixing Data Made Easy for Statistical Analysis
Description:

This package provides a set of functions that facilitate basic data manipulation and cleaning for statistical analysis including functions for finding and fixing duplicate rows and columns, missing values, outliers, and special characters in column and row names and functions for checking data consistency, distribution, quality, reliability, and structure.

r-factoinvestigate 1.9.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://factominer.free.fr/reporting/
Licenses: GPL 2+
Build system: r
Synopsis: Automatic Description of Factorial Analysis
Description:

Brings a set of tools to help and automatically realise the description of principal component analyses (from FactoMineR functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).

r-fmx 0.1.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fmx
Licenses: GPL 2
Build system: r
Synopsis: Finite Mixture Parametrization
Description:

This package provides a parametrization framework for finite mixture distribution using S4 objects. Density, cumulative density, quantile and simulation functions are defined. Currently normal, Tukey g-&-h, skew-normal and skew-t distributions are well tested. The gamma, negative binomial distributions are being tested.

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