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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-fbroc 0.4.1
Propagated dependencies: r-rcpp@1.1.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://www.epeter-stats.de/roc-curve-analysis-with-fbroc/
Licenses: GPL 2
Build system: r
Synopsis: Fast Algorithms to Bootstrap Receiver Operating Characteristics Curves
Description:

This package implements a very fast C++ algorithm to quickly bootstrap receiver operating characteristics (ROC) curves and derived performance metrics, including the area under the curve (AUC) and the partial area under the curve as well as the true and false positive rate. The analysis of paired receiver operating curves is supported as well, so that a comparison of two predictors is possible. You can also plot the results and calculate confidence intervals. On a typical desktop computer the time needed for the calculation of 100000 bootstrap replicates given 500 observations requires time on the order of magnitude of one second.

r-ffaframework 0.1.2
Propagated dependencies: r-patchwork@1.3.2 r-jsonlite@2.0.0 r-httr@1.4.7 r-glue@1.8.0 r-ggplot2@4.0.1 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://rileywheadon.github.io/ffa-framework/
Licenses: AGPL 3+
Build system: r
Synopsis: Flood Frequency Analysis Framework
Description:

This package provides tools to support systematic and reproducible workflows for both stationary and nonstationary flood frequency analysis, with applications extending to other hydroclimate extremes, such as precipitation frequency analysis. This package implements the FFA framework proposed by Vidrio- Sahagún et al. (2024) <doi:10.1016/j.envsoft.2024.105940>, originally developed in MATLAB', now adapted for the R environment. This work was funded by the Flood Hazard Identification and Mapping Program of Environment and Climate Change Canada, as well as the Canada Research Chair (Tier 1) awarded to Dr. Pietroniro.

r-forceplate 1.1-5
Propagated dependencies: r-stringi@1.8.7 r-signal@1.8-1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/RaphaelHartmann/forceplate
Licenses: GPL 2+
Build system: r
Synopsis: Processing Force-Plate Data
Description:

Process raw force-plate data (txt-files) by segmenting them into trials and, if needed, calculating (user-defined) descriptive statistics of variables for user-defined time bins (relative to trigger onsets) for each trial. When segmenting the data a baseline correction, a filter, and a data imputation can be applied if needed. Experimental data can also be processed and combined with the segmented force-plate data. This procedure is suggested by Johannsen et al. (2023) <doi:10.6084/m9.figshare.22190155> and some of the options (e.g., choice of low-pass filter) are also suggested by Winter (2009) <doi:10.1002/9780470549148>.

r-fasano-franceschini-test 2.2.2
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/braunlab-nu/fasano.franceschini.test
Licenses: Expat
Build system: r
Synopsis: Fasano-Franceschini Test: A Multivariate Kolmogorov-Smirnov Two-Sample Test
Description:

An implementation of the two-sample multivariate Kolmogorov-Smirnov test described by Fasano and Franceschini (1987) <doi:10.1093/mnras/225.1.155>. This test evaluates the null hypothesis that two i.i.d. random samples were drawn from the same underlying probability distribution. The data can be of any dimension, and can be of any type (continuous, discrete, or mixed).

r-fractaldim 0.8-5
Propagated dependencies: 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=fractaldim
Licenses: GPL 2+
Build system: r
Synopsis: Estimation of Fractal Dimensions
Description:

This package implements various methods for estimating fractal dimension of time series and 2-dimensional data <doi:10.1214/11-STS370>.

r-frapo 0.4-2
Propagated dependencies: r-timeseries@4041.111 r-rglpk@0.6-5.1 r-cccp@0.3-3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FRAPO
Licenses: GPL 3+
Build system: r
Synopsis: Financial Risk Modelling and Portfolio Optimisation with R
Description:

Accompanying package of the book Financial Risk Modelling and Portfolio Optimisation with R', second edition. The data sets used in the book are contained in this package.

r-frackrigingr 1.0.0
Propagated dependencies: r-psych@2.5.6 r-clustergeneration@1.3.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/NidaGreen/FracKriging
Licenses: GPL 2
Build system: r
Synopsis: Spatial Multivariate Data Modeling
Description:

Aim is to provide fractional Brownian vector field generation algorithm, Hurst parameter estimation method and fractional kriging model for multivariate data modeling.

r-fgarch 4052.93
Propagated dependencies: r-timeseries@4041.111 r-timedate@4051.111 r-matrix@1.7-4 r-fbasics@4041.97 r-fastica@1.2-7 r-cvar@0.6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://geobosh.github.io/fGarchDoc/
Licenses: GPL 2+
Build system: r
Synopsis: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Description:

Analyze and model heteroskedastic behavior in financial time series.

r-fusionchartsr 1.2.0
Propagated dependencies: r-shiny@1.11.1 r-scales@1.4.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-htmlwidgets@1.6.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://alexym1.github.io/fusionchartsR/
Licenses: Expat
Build system: r
Synopsis: Embedding FusionCharts in R
Description:

FusionCharts provides awesome and minimalist functions to make beautiful interactive charts <https://www.fusioncharts.com/>.

r-forestdisc 0.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=ForestDisc
Licenses: GPL 3+
Build system: r
Synopsis: Forest Discretization
Description:

Supervised, multivariate, and non-parametric discretization algorithm based on tree ensembles learning and moment matching optimization. This version of the algorithm relies on random forest algorithm to learn a large set of split points that conserves the relationship between attributes and the target class, and on moment matching optimization to transform this set into a reduced number of cut points matching as well as possible statistical properties of the initial set of split points. For each attribute to be discretized, the set S of its related split points extracted through random forest is mapped to a reduced set C of cut points of size k. This mapping relies on minimizing, for each continuous attribute to be discretized, the distance between the four first moments of S and the four first moments of C subject to some constraints. This non-linear optimization problem is performed using k values ranging from 2 to max_splits', and the best solution returned correspond to the value k which optimum solution is the lowest one over the different realizations. ForestDisc is a generalization of RFDisc discretization method initially proposed by Berrado and Runger (2009) <doi:10.1109/AICCSA.2009.5069327>, and improved by Berrado et al. in 2012 by adopting the idea of moment matching optimization related by Hoyland and Wallace (2001) <doi: 10.1287/mnsc.47.2.295.9834>.

r-forestgym 1.0.0
Propagated dependencies: r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=forestGYM
Licenses: GPL 2
Build system: r
Synopsis: Forest Growth and Yield Model Based on Clutter Model
Description:

The Clutter model is a significant forest growth simulation tool. Grounded on individual trees and comprehensively considering factors such as competition among trees and the impact of environmental elements on growth, it can accurately reflect the growth process of forest stands. It can be applied in areas like forest resource management, harvesting planning, and ecological research. With the help of the Clutter model, people can better understand the dynamic changes of forests and provide a scientific basis for rational forest management and protecting the ecological environment. This R package can effectively realize the construction of forest growth and harvest models based on the Clutter model and achieve optimized forest management.References: Farias A, Soares C, Leite H et al(2021)<doi:10.1007/s10342-021-01380-1>. Guera O, Silva J, Ferreira R, et al(2019)<doi:10.1590/2179-8087.038117>.

r-fdapde 1.1-21
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fdaPDE
Licenses: GPL 3
Build system: r
Synopsis: Physics-Informed Spatial and Functional Data Analysis
Description:

An implementation of regression models with partial differential regularizations, making use of the Finite Element Method. The models efficiently handle data distributed over irregularly shaped domains and can comply with various conditions at the boundaries of the domain. A priori information about the spatial structure of the phenomenon under study can be incorporated in the model via the differential regularization. See Sangalli, L. M. (2021) <doi:10.1111/insr.12444> "Spatial Regression With Partial Differential Equation Regularisation" for an overview. The release 1.1-9 requires R (>= 4.2.0) to be installed on windows machines.

r-fairsubset 1.0
Propagated dependencies: r-matrixstats@1.5.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://pubmed.ncbi.nlm.nih.gov/31583263/
Licenses: GPL 3
Build system: r
Synopsis: Choose Representative Subsets
Description:

Allows user to obtain subsets of columns of data or vectors within a list. These subsets will match the original data in terms of average and variation, but have a consistent length of data per column. It is intended for use on automated data generation which may not always output the same N per replicate or sample.

r-firesafety 0.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/thomasp85/firesafety
Licenses: Expat
Build system: r
Synopsis: Collection of Security Related Plugins for 'fiery'
Description:

Provide a range of plugins for fiery web servers that handle different aspects of server-side web security. Be aware that security cannot be handled blindly, and even though these plugins will raise the security of your server you should not build critical infrastructure without the aid of a security expert.

r-foresttools 1.0.3
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-matrix@1.7-4 r-imager@1.0.5 r-glcmtextures@0.6.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/andrew-plowright/ForestTools
Licenses: GPL 3
Build system: r
Synopsis: Tools for Analyzing Remote Sensing Forest Data
Description:

This package provides tools for analyzing remote sensing forest data, including functions for detecting treetops from canopy models, outlining tree crowns, and calculating textural metrics.

r-firesale 0.1.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/thomasp85/firesale
Licenses: Expat
Build system: r
Synopsis: Datastore for 'fiery' Web Servers
Description:

This package provides a persistent datastore for fiery apps. The datastore is build on top of the storr package and can thus be based on a variety of backends. The datastore contains both a global and session-scoped section.

r-faulttree 1.0.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://www.openreliability.org/fault-tree-analysis-on-r/
Licenses: GPL 3+
Build system: r
Synopsis: Fault Trees for Risk and Reliability Analysis
Description:

Construction, calculation and display of fault trees. Methods derived from Clifton A. Ericson II (2005, ISBN: 9780471739425) <DOI:10.1002/0471739421>, Antoine Rauzy (1993) <DOI:10.1016/0951-8320(93)90060-C>, Tim Bedford and Roger Cooke (2012, ISBN: 9780511813597) <DOI:10.1017/CBO9780511813597>, Nikolaos Limnios, (2007, ISBN: 9780470612484) <DOI: 10.1002/9780470612484>.

r-folda 0.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/Moran79/folda
Licenses: Expat
Build system: r
Synopsis: Forward Stepwise Discriminant Analysis with Pillai's Trace
Description:

This package provides a novel forward stepwise discriminant analysis framework that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA), providing an improvement over traditional stepwise LDA methods that rely on Wilks Lambda. A stand-alone ULDA implementation is also provided, offering a more general solution than the one available in the MASS package. It automatically handles missing values and provides visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2409.03136>.

r-foragingorg 0.1.0
Propagated dependencies: r-tsp@1.2.6 r-pairviz@1.3.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=ForagingOrg
Licenses: GPL 3
Build system: r
Synopsis: Organization Measures for Visual Foraging
Description:

Several functions to compute indicators for organization and efficiency in visual foraging, multi-target visual search, and cancellation tasks. The current version of this package includes the following indicators: best-r, mean Inter-target Distance, Percentage Above Optimal (PAO) scan path, and intersections in the scan path. For more detailed descriptions, see Mark et al. (2004) <doi:10.1212/01.WNL.0000131947.08670.D4>.

r-frk 2.3.2
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://andrewzm.github.io/FRK/
Licenses: GPL 2+
Build system: r
Synopsis: Fixed Rank Kriging
Description:

This package provides a tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of basis functions. This fixed-rank basis-function representation facilitates the modelling of big data, and the method naturally allows for non-stationary, anisotropic covariance functions. Discretisation of the spatial domain into so-called basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both point-referenced and areal supports, potentially simultaneously), and prediction over arbitrary user-specified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above also supports the modelling of non-Gaussian data (e.g., Poisson, binomial, negative-binomial, gamma, and inverse-Gaussian) by employing a generalised linear mixed model (GLMM) framework. Zammit-Mangion and Cressie <doi:10.18637/jss.v098.i04> describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs, while Sainsbury-Dale, Zammit-Mangion, and Cressie <doi:10.18637/jss.v108.i10> describe `FRK` in a non-Gaussian setting; two vignettes are available that summarise these papers and provide additional examples.

r-fastkqr 1.0.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fastkqr
Licenses: GPL 2
Build system: r
Synopsis: Fast Algorithm for Kernel Quantile Regression
Description:

An efficient algorithm to fit and tune kernel quantile regression models based on the majorization-minimization (MM) method. It can also fit multiple quantile curves simultaneously without crossing.

r-famish 0.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://famish.probaverse.com/
Licenses: Expat
Build system: r
Synopsis: Flexibly Tune Families of Probability Distributions
Description:

Fits probability distributions to data and plugs into the probaverse suite of R packages so distribution objects are ready for further manipulation and evaluation. Supports methods such as maximum likelihood and L-moments, and provides diagnostics including empirical ranking and quantile score.

r-fresa-cad 3.4.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FRESA.CAD
Licenses: LGPL 2.0+
Build system: r
Synopsis: Feature Selection Algorithms for Computer Aided Diagnosis
Description:

This package contains a set of utilities for building and testing statistical models (linear, logistic,ordinal or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.

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>.

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Total results: 69112