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    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
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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-flashier 1.0.7
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/willwerscheid/flashier
Licenses: Modified BSD
Build system: r
Synopsis: Empirical Bayes Matrix Factorization
Description:

This package provides methods for matrix factorization based on Wang and Stephens (2021) <https://jmlr.org/papers/v22/20-589.html>.

r-fueldeep3d 0.1.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/venkatasivanaga/FuelDeep3D
Licenses: GPL 3+
Build system: r
Synopsis: 3D Fuel Segmentation Using Terrestrial Laser Scanning and Deep Learning
Description:

This package provides tools for preprocessing, feature extraction, and segmentation of three-dimensional forest point clouds derived from terrestrial laser scanning. Functions support creating height-above-ground (HAG) metrics, tiling, and sampling point clouds, generating training datasets, applying trained models to new point clouds, and producing per-point fuel classes such as stems, branches, foliage, and surface fuels. These tools support workflows for forest structure analysis, wildfire behavior modeling, and fuel complexity assessment. Deep learning segmentation relies on the PointNeXt architecture described by Qian et al. (2022) <doi:10.48550/arXiv.2206.04670>, while ground classification utilizes the Cloth Simulation Filter algorithm by Zhang et al. (2016) <doi:10.3390/rs8060501>.

r-fnets 0.1.6
Propagated dependencies: r-rcolorbrewer@1.1-3 r-mass@7.3-65 r-lpsolve@5.6.23 r-igraph@2.2.1 r-foreach@1.5.2 r-fields@17.1 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-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-fastrg 0.4.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://rohelab.github.io/fastRG/
Licenses: Expat
Build system: r
Synopsis: Sample Generalized Random Dot Product Graphs in Linear Time
Description:

Samples generalized random product graphs, a generalization of a broad class of network models. Given matrices X, S, and Y with with non-negative entries, samples a matrix with expectation X S Y^T and independent Poisson or Bernoulli entries using the fastRG algorithm of Rohe et al. (2017) <https://www.jmlr.org/papers/v19/17-128.html>. The algorithm first samples the number of edges and then puts them down one-by-one. As a result it is O(m) where m is the number of edges, a dramatic improvement over element-wise algorithms that which require O(n^2) operations to sample a random graph, where n is the number of nodes.

r-fpcompare 0.2.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/PredictiveEcology/fpCompare
Licenses: GPL 3
Build system: r
Synopsis: Reliable Comparison of Floating Point Numbers
Description:

Comparisons of floating point numbers are problematic due to errors associated with the binary representation of decimal numbers. Despite being aware of these problems, people still use numerical methods that fail to account for these and other rounding errors (this pitfall is the first to be highlighted in Circle 1 of Burns (2012) The R Inferno <https://www.burns-stat.com/pages/Tutor/R_inferno.pdf>). This package provides new relational operators useful for performing floating point number comparisons with a set tolerance.

r-farrell 0.2.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/feddelegrand7/farrell
Licenses: Expat
Build system: r
Synopsis: Interactive Interface to Data Envelopment Analysis Modeling
Description:

Allows the user to execute interactively radial data envelopment analysis models. The user has the ability to upload a data frame, select the input/output variables, choose the technology assumption to adopt and decide whether to run an input or an output oriented model. When the model is executed a set of results are displayed which include efficiency scores, peers determination, scale efficiencies evaluation and slacks calculation. Fore more information about the theoretical background of the package, please refer to Bogetoft & Otto (2011) <doi:10.1007/978-1-4419-7961-2>.

r-fgeo-tool 1.2.10
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://forestgeo.github.io/fgeo.tool/
Licenses: GPL 3
Build system: r
Synopsis: Import and Manipulate '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 easily import, filter, and modify ForestGEO data. To learn more about ForestGEO visit <https://forestgeo.si.edu/>.

r-fractd 0.1.0
Propagated dependencies: r-plyr@1.8.9 r-imager@1.0.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fractD
Licenses: GPL 3
Build system: r
Synopsis: Estimation of Fractal Dimension of a Black Area in 2D and 3D (Slices) Images
Description:

Estimate the of fractal dimension of a black area in 2D and 3D (slices) images using the box-counting method. See Klinkenberg B. (1994) <doi:10.1007/BF02065874>.

r-freqdom 2.0.5
Propagated dependencies: r-mvtnorm@1.3-3 r-matrixcalc@1.0-6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=freqdom
Licenses: GPL 3
Build system: r
Synopsis: Frequency Domain Based Analysis: Dynamic PCA
Description:

Implementation of dynamic principal component analysis (DPCA), simulation of VAR and VMA processes and frequency domain tools. These frequency domain methods for dimensionality reduction of multivariate time series were introduced by David Brillinger in his book Time Series (1974). We follow implementation guidelines as described in Hormann, Kidzinski and Hallin (2016), Dynamic Functional Principal Component <doi:10.1111/rssb.12076>.

r-frontmatter 0.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/posit-dev/frontmatter
Licenses: Expat
Build system: r
Synopsis: Parse Front Matter from Documents
Description:

Extracts and parses structured metadata ('YAML or TOML') from the beginning of text documents. Front matter is a common pattern in Quarto documents, R Markdown documents, static site generators, documentation systems, content management tools and even Python and R scripts where metadata is placed at the top of a document, separated from the main content by delimiter fences.

r-faraway 1.0.9
Propagated dependencies: r-nlme@3.1-168 r-lme4@1.1-37
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/julianfaraway/faraway
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Datasets and Functions for Books by Julian Faraway
Description:

Books are "Linear Models with R" published 1st Ed. August 2004, 2nd Ed. July 2014, 3rd Ed. February 2025 by CRC press, ISBN 9781439887332, and "Extending the Linear Model with R" published by CRC press in 1st Ed. December 2005 and 2nd Ed. March 2016, ISBN 9781584884248 and "Practical Regression and ANOVA in R" contributed documentation on CRAN (now very dated).

r-funcmap 1.0.10
Propagated dependencies: r-mvbutils@2.8.232
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FuncMap
Licenses: GPL 3
Build system: r
Synopsis: Hive Plots of R Package Function Calls
Description:

Analyzes the function calls in an R package and creates a hive plot of the calls, dividing them among functions that only make outgoing calls (sources), functions that have only incoming calls (sinks), and those that have both incoming calls and make outgoing calls (managers). Function calls can be mapped by their absolute numbers, their normalized absolute numbers, or their rank. FuncMap should be useful for comparing packages at a high level for their overall design. Plus, it's just plain fun. The hive plot concept was developed by Martin Krzywinski (www.hiveplot.com) and inspired this package. Note: this package is maintained for historical reasons. HiveR is a full package for creating hive plots.

r-fincal 0.6.3
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-fenmlm 2.4.4
Propagated dependencies: r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-mass@7.3-65 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FENmlm
Licenses: GPL 2+
Build system: r
Synopsis: Fixed Effects Nonlinear Maximum Likelihood Models
Description:

Efficient estimation of maximum likelihood models with multiple fixed-effects. Standard-errors can easily and flexibly be clustered and estimations exported.

r-fieldhub 1.5.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/DidierMurilloF/FielDHub
Licenses: Expat
Build system: r
Synopsis: Shiny App for Design of Experiments in Life Sciences
Description:

This package provides a shiny design of experiments (DOE) app that aids in the creation of traditional, un-replicated, augmented and partially-replicated designs applied to agriculture, plant breeding, forestry, animal and biological sciences.

r-feprovider 1.1
Propagated dependencies: r-poibin@1.6 r-matrix@1.7-4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FEprovideR
Licenses: GPL 2
Build system: r
Synopsis: Fixed Effects Logistic Model with High-Dimensional Parameters
Description:

This package provides a structured profile likelihood algorithm for the logistic fixed effects model and an approximate expectation maximization (EM) algorithm for the logistic mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) <doi:10.1007/s10985-013-9264-6>.

r-fastlogisticregressionwrap 1.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/kapelner/fastLogisticRegressionWrap
Licenses: GPL 3
Build system: r
Synopsis: Fast Logistic Regression Wrapper
Description:

This package provides very fast logistic regression with coefficient inferences plus other useful methods such as a forward stepwise model generator (see the benchmarks by visiting the github page at the URL below). The inputs are flexible enough to accomodate GPU computations. The coefficient estimation employs the fastLR() method in the RcppNumerical package by Yixuan Qiu et al. This package allows their work to be more useful to a wider community that consumes inference.

r-fundiversity 1.1.1
Propagated dependencies: r-vegan@2.7-2 r-matrix@1.7-4 r-geometry@0.5.2 r-future-apply@1.20.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://funecology.github.io/fundiversity/
Licenses: GPL 3
Build system: r
Synopsis: Easy Computation of Functional Diversity Indices
Description:

Computes six functional diversity indices. These are namely, Functional Divergence (FDiv), Function Evenness (FEve), Functional Richness (FRic), Functional Richness intersections (FRic_intersect), Functional Dispersion (FDis), and Rao's entropy (Q) (reviewed in Villéger et al. 2008 <doi:10.1890/07-1206.1>). Provides efficient, modular, and parallel functions to compute functional diversity indices (preprint: <doi:10.32942/osf.io/dg7hw>).

r-fpca3d 1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FPCA3D
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Three Dimensional Functional Component Analysis
Description:

Run three dimensional functional principal component analysis and return the three dimensional functional principal component scores. The details of the method are explained in Lin et al.(2015) <doi:10.1371/journal.pone.0132945>.

r-freqparcoord 1.0.1
Propagated dependencies: r-mvtnorm@1.3-3 r-ggplot2@4.0.1 r-ggally@2.4.0 r-fnn@1.1.4.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=freqparcoord
Licenses: GPL 2+
Build system: r
Synopsis: Novel Methods for Parallel Coordinates
Description:

New approaches to parallel coordinates plots for multivariate data visualization, including applications to clustering, outlier hunting and regression diagnostics. Includes general functions for multivariate nonparametric density and regression estimation, using parallel computation.

r-fselectorrcpp 0.3.13
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/mi2-warsaw/FSelectorRcpp
Licenses: GPL 2
Build system: r
Synopsis: 'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support
Description:

Rcpp (free of Java'/'Weka') implementation of FSelector entropy-based feature selection algorithms based on an MDL discretization (Fayyad U. M., Irani K. B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. In 13'th International Joint Conference on Uncertainly in Artificial Intelligence (IJCAI93), pages 1022-1029, Chambery, France, 1993.) <https://www.ijcai.org/Proceedings/93-2/Papers/022.pdf> with a sparse matrix support.

r-fastwavelets 1.0.1
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/johnswyou/fastWavelets
Licenses: Expat
Build system: r
Synopsis: Compute Maximal Overlap Discrete Wavelet Transform (MODWT) and À Trous Discrete Wavelet Transform
Description:

This package provides a lightweight package to compute Maximal Overlap Discrete Wavelet Transform (MODWT) and à Trous Discrete Wavelet Transform by leveraging the power of Rcpp to make these operations fast. This package was designed for use in forecasting, and allows users avoid the inclusion of future data when performing wavelet decomposition of time series. See Quilty and Adamowski (2018) <doi:10.1016/j.jhydrol.2018.05.003>.

r-fairml 0.9
Propagated dependencies: r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fairml
Licenses: Expat
Build system: r
Synopsis: Fair Models in Machine Learning
Description:

Fair machine learning regression models which take sensitive attributes into account in model estimation. Currently implementing Komiyama et al. (2018) <http://proceedings.mlr.press/v80/komiyama18a/komiyama18a.pdf>, Zafar et al. (2019) <https://www.jmlr.org/papers/volume20/18-262/18-262.pdf> and my own approach from Scutari, Panero and Proissl (2022) <doi:10.1007/s11222-022-10143-w> that uses ridge regression to enforce fairness.

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