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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 search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-flowchart 1.0.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.2 r-tibble@3.3.1 r-stringr@1.6.0 r-rlang@1.2.0 r-purrr@1.2.2 r-gmisc@3.2.0 r-dplyr@1.2.1 r-cli@3.6.6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://bruigtp.github.io/flowchart/
Licenses: GPL 3+
Build system: r
Synopsis: Tidy Flowchart Generator
Description:

This package creates participant flow diagrams directly from a dataframe. Representing the flow of participants through each stage of a study, especially in clinical trials, is essential to assess the generalisability and validity of the results. This package provides a set of functions that can be combined with a pipe operator to create all kinds of flowcharts from a data frame in an easy way.

r-frailtyem 1.0.1
Propagated dependencies: r-tibble@3.3.1 r-survival@3.8-6 r-rcpp@1.1.1-1.1 r-numderiv@2016.8-1.1 r-msm@1.8.2 r-matrix@1.7-5 r-magrittr@2.0.5 r-ggplot2@4.0.3 r-expint@0.2-1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/tbalan/frailtyEM
Licenses: GPL 2+
Build system: r
Synopsis: Fitting Frailty Models with the EM Algorithm
Description:

This package contains functions for fitting shared frailty models with a semi-parametric baseline hazard with the Expectation-Maximization algorithm. Supported data formats include clustered failures with left truncation and recurrent events in gap-time or Andersen-Gill format. Several frailty distributions, such as the the gamma, positive stable and the Power Variance Family are supported.

r-flickrapi 0.1.0.1
Propagated dependencies: r-rlang@1.2.0 r-magrittr@2.0.5 r-janitor@2.2.1 r-httr2@1.2.2
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FlickrAPI
Licenses: GPL 3+
Build system: r
Synopsis: Access to Flickr API
Description:

This package provides an interface to the Flickr API <https://www.flickr.com/services/api/> and allows R users to download data on Flickr.

r-fake 1.5.0
Propagated dependencies: r-withr@3.0.2 r-rdpack@2.6.6 r-mass@7.3-65 r-igraph@2.3.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fake
Licenses: GPL 3+
Build system: r
Synopsis: Flexible Data Simulation Using the Multivariate Normal Distribution
Description:

This R package can be used to generate artificial data conditionally on pre-specified (simulated or user-defined) relationships between the variables and/or observations. Each observation is drawn from a multivariate Normal distribution where the mean vector and covariance matrix reflect the desired relationships. Outputs can be used to evaluate the performances of variable selection, graphical modelling, or clustering approaches by comparing the true and estimated structures (B Bodinier et al (2021) <doi:10.1093/jrsssc/qlad058>).

r-fincal 0.6.3
Propagated dependencies: r-reshape2@1.4.5 r-rcurl@1.98-1.18 r-ggplot2@4.0.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://felixfan.github.io/FinCal/
Licenses: GPL 2+
Build system: r
Synopsis: Time Value of Money, Time Series Analysis and Computational Finance
Description:

Package for time value of money calculation, time series analysis and computational finance.

r-fusionlearn 0.2.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FusionLearn
Licenses: GPL 2+
Build system: r
Synopsis: Fusion Learning
Description:

The fusion learning method uses a model selection algorithm to learn from multiple data sets across different experimental platforms through group penalization. The responses of interest may include a mix of discrete and continuous variables. The responses may share the same set of predictors, however, the models and parameters differ across different platforms. Integrating information from different data sets can enhance the power of model selection. Package is based on Xin Gao, Raymond J. Carroll (2017) <arXiv:1610.00667v1>.

r-fdaconcur 0.1.3
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.1-1.1 r-fdapace@0.6.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/functionaldata/tFDAconcur
Licenses: Modified BSD
Build system: r
Synopsis: Concurrent Regression and History Index Models for Functional Data
Description:

This package provides an implementation of concurrent or varying coefficient regression methods for functional data. The implementations are done for both dense and sparsely observed functional data. Pointwise confidence bands can be constructed for each case. Further, the influence of past predictor values are modeled by a smooth history index function, while the effects on the response are described by smooth varying coefficient functions, which are very useful in analyzing real data such as COVID data. References: Yao, F., Müller, H.G., Wang, J.L. (2005) <doi:10.1214/009053605000000660>. Sentürk, D., Müller, H.G. (2010) <doi:10.1198/jasa.2010.tm09228>.

r-fourinarow 0.1.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fourinarow
Licenses: Expat
Build system: r
Synopsis: Play "Four in a Row"
Description:

Play or simulate games of "Four in a Row" in the R console. This package is designed for educational purposes, encouraging users to write their own functions to play the game automatically. It contains a collection of built-in functions that play the game at various skill levels, for users to test their own functions against.

r-fnets 0.1.6
Propagated dependencies: r-rcolorbrewer@1.1-3 r-mass@7.3-65 r-lpsolve@5.6.23 r-igraph@2.3.1 r-foreach@1.5.2 r-fields@17.3 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fnets
Licenses: GPL 3+
Build system: r
Synopsis: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series
Description:

This package implements methods for network estimation and forecasting of high-dimensional time series exhibiting strong serial and cross-sectional correlations under a factor-adjusted vector autoregressive model. See Barigozzi, Cho and Owens (2024+) <doi:10.1080/07350015.2023.2257270> for further descriptions of FNETS methodology and Owens, Cho and Barigozzi (2024+) <arXiv:2301.11675> accompanying the R package.

r-fri 1.0
Propagated dependencies: r-rsnns@0.4-18 r-neuralnet@1.44.2 r-ggplot2@4.0.3 r-forcats@1.0.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FRI
Licenses: Expat
Build system: r
Synopsis: Relative Importance of Main and Interaction Effects
Description:

Computes relative importance of main and interaction effects. Also, sum of the modified generalized weights is computed. Ibrahim et al. (2022) <doi:10.1134/S1064229322080051>.

r-frapp 1.0.0
Propagated dependencies: r-shiny@1.13.0 r-nlme@3.1-169 r-gplots@3.3.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/gioiadc/FRApp
Licenses: GPL 3+
Build system: r
Synopsis: FRAP Data Analysis Using Nonlinear Mixed Effect Models with 'shiny'
Description:

Analysis of Fluorescence Recovery After Photobleaching (FRAP) experiments using nonlinear mixed-effects regression models and analysis of the results. FRApp is not limited to the analysis of FRAP experiments only. Any nonlinear mixed-effects models with an asymptotic exponential functional relationship to hierarchical data in various domains can be fitted. The analysis of data available in the package is presented in Di Credico, G., Pelucchi, S., Pauli, F. et al. (2025) <doi:10.1038/s41598-025-87154-w>.

r-fhircrackr 2.4.0
Propagated dependencies: r-xml2@1.5.2 r-stringr@1.6.0 r-rlang@1.2.0 r-lifecycle@1.0.5 r-httr@1.4.8 r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fhircrackr
Licenses: GPL 3
Build system: r
Synopsis: Handling HL7 FHIR® Resources in R
Description:

Useful tools for conveniently downloading FHIR resources in xml format and converting them to R data.frames. Uses FHIR-search to download bundles from a FHIR server, provides functions to save and read xml-files containing such bundles and allows flattening the bundles to data.frames using XPath expressions. FHIR® is the registered trademark of HL7 and is used with the permission of HL7. Use of the FHIR trademark does not constitute endorsement of this product by HL7.

r-fhdi 1.4.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://www.r-project.org
Licenses: GPL 2+
Build system: r
Synopsis: Fractional Hot Deck and Fully Efficient Fractional Imputation
Description:

Impute general multivariate missing data with the fractional hot deck imputation based on Jaekwang Kim (2011) <doi:10.1093/biomet/asq073>.

r-flexlsx 1.0.0
Propagated dependencies: r-tidyr@1.3.2 r-tibble@3.3.1 r-stringi@1.8.7 r-rlang@1.2.0 r-rcpp@1.1.1-1.1 r-purrr@1.2.2 r-openxlsx2@1.29 r-dplyr@1.2.1
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-forecastdom 0.1.0
Propagated dependencies: r-rcpp@1.1.1-1.1 r-mass@7.3-65 r-ggplot2@4.0.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://gabbocg.github.io/forecastdom/
Licenses: Expat
Build system: r
Synopsis: Tools for (Un)Conditional Forecast Dominance
Description:

This package provides a unified toolkit for out-of-sample forecast dominance testing. Covers unconditional and conditional equal and superior predictive ability, encompassing, and nested-model comparison. Implements the Diebold-Mariano test with the Harvey, Leybourne, and Newbold (1997) <doi:10.1016/S0169-2070(96)00719-4> small-sample correction; the Clark-West MSFE-adjusted statistic (Clark and West, 2007) <doi:10.1016/j.jeconom.2006.05.023>; the ENC-NEW encompassing test of Clark and McCracken (2001) <doi:10.1016/S0304-4076(01)00071-9>; the Giacomini-White conditional equal predictive ability test (Giacomini and White, 2006) <doi:10.1111/j.1468-0262.2006.00718.x>; Hansen's superior predictive ability test (Hansen, 2005) <doi:10.1198/073500105000000063>; the conditional superior predictive ability test of Li, Liao, and Quaedvlieg (2022) <doi:10.1093/restud/rdab039>; and the uniform and average multi-horizon SPA tests of Quaedvlieg (2021) <doi:10.1080/07350015.2019.1620074>.

r-fcros 1.6-6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fcros
Licenses: GPL 2+
Build system: r
Synopsis: Method to Search for Differentially Expressed Genes and to Detect Recurrent Chromosomal Copy Number Aberrations
Description:

This package provides a fold change rank based method is presented to search for genes with changing expression and to detect recurrent chromosomal copy number aberrations. This method may be useful for high-throughput biological data (micro-array, sequencing, ...). Probabilities are associated with genes or probes in the data set and there is no problem of multiple tests when using this method. For array-based comparative genomic hybridization data, segmentation results are obtained by merging the significant probes detected.

r-flora 0.3.4
Propagated dependencies: r-stringdist@0.9.17 r-jsonlite@2.0.0 r-httr@1.4.8 r-dplyr@1.2.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://www.github.com/gustavobio/flora
Licenses: GPL 2+
Build system: r
Synopsis: Tools for Interacting with the Brazilian Flora 2020
Description:

This package provides tools to quickly compile taxonomic and distribution data from the Brazilian Flora 2020.

r-fmt 2.0
Propagated dependencies: r-limma@3.68.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fmt
Licenses: GPL 2
Build system: r
Synopsis: Variance Estimation of FMT Method (Fully Moderated T-Statistic)
Description:

The FMT method computes posterior residual variances to be used in the denominator of a moderated t-statistic from a linear model analysis of gene expression data. It is an extension of the moderated t-statistic originally proposed by Smyth (2004) <doi:10.2202/1544-6115.1027>. LOESS local regression and empirical Bayesian method are used to estimate gene specific prior degrees of freedom and prior variance based on average gene intensity levels. The posterior residual variance in the denominator is a weighted average of prior and residual variance and the weights are prior degrees of freedom and residual variance degrees of freedom. The degrees of freedom of the moderated t-statistic is simply the sum of prior and residual variance degrees of freedom.

r-formulaic 0.0.8
Propagated dependencies: r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://dachosen1.github.io/formulaic/index.html
Licenses: GPL 3
Build system: r
Synopsis: Dynamic Generation and Quality Checks of Formula Objects
Description:

Many statistical models and analyses in R are implemented through formula objects. The formulaic package creates a unified approach for programmatically and dynamically generating formula objects. Users may specify the outcome and inputs of a model directly, search for variables to include based upon naming patterns, incorporate interactions, and identify variables to exclude. A wide range of quality checks are implemented to identify issues such as misspecified variables, duplication, a lack of contrast in the inputs, and a large number of levels in categorical data. Variables that do not meet these quality checks can be automatically excluded from the model. These issues are documented and reported in a manner that provides greater accountability and useful information to guide an investigation of the data.

r-featurecormatrix 0.4.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=featureCorMatrix
Licenses: GPL 2+
Build system: r
Synopsis: Measurement Level Independent Feature Correlation Matrix
Description:

Uses three different correlation coefficients to calculate measurement-level adequate correlations in a feature matrix: Pearson product-moment correlation coefficient, Intraclass correlation and Cramer's V.

r-fsr 2.0.1
Propagated dependencies: r-tibble@3.3.1 r-stringr@1.6.0 r-sf@1.1-1 r-rlang@1.2.0 r-pso@1.0.4 r-ggplot2@4.0.3 r-e1071@1.7-17 r-dplyr@1.2.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://accarniel.github.io/fsr/
Licenses: GPL 3
Build system: r
Synopsis: Handling Fuzzy Spatial Data
Description:

Support for fuzzy spatial objects, their operations, and fuzzy spatial inference models based on Spatial Plateau Algebra. It employs fuzzy set theory and fuzzy logic as foundation to deal with spatial fuzziness. It mainly implements underlying concepts defined in the following research papers: (i) "Spatial Plateau Algebra: An Executable Type System for Fuzzy Spatial Data Types" <doi:10.1109/FUZZ-IEEE.2018.8491565>; (ii) "A Systematic Approach to Creating Fuzzy Region Objects from Real Spatial Data Sets" <doi:10.1109/FUZZ-IEEE.2019.8858878>; (iii) "Spatial Data Types for Heterogeneously Structured Fuzzy Spatial Collections and Compositions" <doi:10.1109/FUZZ48607.2020.9177620>; (iv) "Fuzzy Inference on Fuzzy Spatial Objects (FIFUS) for Spatial Decision Support Systems" <doi:10.1109/FUZZ-IEEE.2017.8015707>; (v) "Evaluating Region Inference Methods by Using Fuzzy Spatial Inference Models" <doi:10.1109/FUZZ-IEEE55066.2022.9882658>.

r-fda-vi 1.0.0
Propagated dependencies: r-scales@1.4.0 r-mass@7.3-65 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/desouzalab/fda.vi
Licenses: Expat
Build system: r
Synopsis: Functional Data Analysis using Variational Inference
Description:

This package implements a variational Expectation-Maximization (VEM) algorithm for smoothing one or multiple functional observations via basis function selection. The algorithm estimates all model parameters simultaneously and automatically, while accounting for within-curve correlation. The approach provides a flexible and computationally efficient framework for smoothing correlated functional data. The algorithm is described in da Cruz, A. C., de Souza, C. P., and Sousa, P. H. (2024). Fast Bayesian basis selection for functional data representation with correlated errors. <doi:10.48550/arXiv.2405.20758>.

r-fracprolif 1.0.7
Propagated dependencies: r-numderiv@2016.8-1.1 r-emg@1.0.9
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fracprolif
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Fraction Proliferation via a Quiescent Growth Model
Description:

This package provides functions for fitting data to a quiescent growth model, i.e. a growth process that involves members of the population who stop dividing or propagating.

r-fincovregularization 1.1.0
Propagated dependencies: r-quadprog@1.5-8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://github.com/yanyachen/FinCovRegularization
Licenses: GPL 2
Build system: r
Synopsis: Covariance Matrix Estimation and Regularization for Finance
Description:

Estimation and regularization for covariance matrix of asset returns. For covariance matrix estimation, three major types of factor models are included: macroeconomic factor model, fundamental factor model and statistical factor model. For covariance matrix regularization, four regularized estimators are included: banding, tapering, hard-thresholding and soft- thresholding. The tuning parameters of these regularized estimators are selected via cross-validation.

Total packages: 73955