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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-fmstable 0.1-4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FMStable
Licenses: GPL 3
Build system: r
Synopsis: Finite Moment Stable Distributions
Description:

Some basic procedures for dealing with log maximally skew stable distributions, which are also called finite moment log stable distributions.

r-ffmanova 1.1.2
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/olangsrud/ffmanova
Licenses: GPL 2
Build system: r
Synopsis: Fifty-Fifty MANOVA
Description:

General linear modeling with multiple responses (MANCOVA). An overall p-value for each model term is calculated by the 50-50 MANOVA method by Langsrud (2002) <doi:10.1111/1467-9884.00320>, which handles collinear responses. Rotation testing, described by Langsrud (2005) <doi:10.1007/s11222-005-4789-5>, is used to compute adjusted single response p-values according to familywise error rates and false discovery rates (FDR). The approach to FDR is described in the appendix of Moen et al. (2005) <doi:10.1128/AEM.71.4.2086-2094.2005>. Unbalanced designs are handled by Type II sums of squares as argued in Langsrud (2003) <doi:10.1023/A:1023260610025>. Furthermore, the Type II philosophy is extended to continuous design variables as described in Langsrud et al. (2007) <doi:10.1080/02664760701594246>. This means that the method is invariant to scale changes and that common pitfalls are avoided.

r-flag 0.1
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/YangLabHKUST/FLAG
Licenses: Expat
Build system: r
Synopsis: Flexible and Accurate Gaussian Graphical Models
Description:

In order to achieve accurate estimation without sparsity assumption on the precision matrix, element-wise inference on the precision matrix, and joint estimation of multiple Gaussian graphical models, a novel method is proposed and efficient algorithm is implemented. FLAG() is the main function given a data matrix, and FlagOneEdge() will be used when one pair of random variables are interested where their indices should be given. Flexible and Accurate Methods for Estimation and Inference of Gaussian Graphical Models with Applications, see Qian Y (2023) <doi:10.14711/thesis-991013223054603412>, Qian Y, Hu X, Yang C (2023) <doi:10.48550/arXiv.2306.17584>.

r-flood 0.1.1
Propagated dependencies: r-tlmoments@0.7.5.3 r-magrittr@2.0.4 r-evd@2.3-7.1 r-copula@1.1-6
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=flood
Licenses: GPL 2+
Build system: r
Synopsis: Statistical Methods for the (Regional) Analysis of Flood Frequency
Description:

Includes several statistical methods for the estimation of parameters and high quantiles of river flow distributions. The focus is on regional estimation based on homogeneity assumptions and computed from multivariate observations (multiple measurement stations). For details see Kinsvater et al. (2017) <arXiv:1701.06455>.

r-floral 0.7.0
Propagated dependencies: r-survival@3.8-3 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-fable-ata 0.0.6
Propagated dependencies: r-tsibble@1.2.0 r-tsbox@0.4.2 r-tibble@3.3.0 r-rlang@1.1.6 r-lubridate@1.9.4 r-fabletools@0.6.0 r-dplyr@1.1.4 r-distributional@0.5.0 r-ataforecasting@0.0.61
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-fgalgorithm 1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FGalgorithm
Licenses: GPL 2+
Build system: r
Synopsis: Flury and Gautschi algorithms
Description:

This is a package for implementation of Flury-Gautschi algorithms.

r-fkf-sp 0.3.4
Propagated dependencies: r-mathjaxr@1.8-0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/TomAspinall/FKF.SP
Licenses: GPL 3
Build system: r
Synopsis: Fast Kalman Filtering Through Sequential Processing
Description:

Fast and flexible Kalman filtering and smoothing implementation utilizing sequential processing, designed for efficient parameter estimation through maximum likelihood estimation. Sequential processing is a univariate treatment of a multivariate series of observations and can benefit from computational efficiency over traditional Kalman filtering when independence is assumed in the variance of the disturbances of the measurement equation. Sequential processing is described in the textbook of Durbin and Koopman (2001, ISBN:978-0-19-964117-8). FKF.SP was built upon the existing FKF package and is, in general, a faster Kalman filter/smoother.

r-filters 0.3.1
Propagated dependencies: r-yaml@2.3.10 r-plyr@1.8.9 r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=filters
Licenses: ASL 2.0
Build system: r
Synopsis: "Snake_case" Filter System for R
Description:

Enables filtering datasets by a prior specified identifiers which correspond to saved filter expressions.

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-forensim 4.3.3
Propagated dependencies: r-tkrplot@0.0-30 r-tcltk2@1.6.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=forensim
Licenses: GPL 2+
Build system: r
Synopsis: Interpretation of Forensic DNA Mixtures
Description:

Statistical methods and simulation tools for the interpretation of forensic DNA mixtures. The methods implemented are described in Haned et al. (2011) <doi:10.1111/j.1556-4029.2010.01550.x>, Haned et al. (2012) <doi:10.1016/j.fsigen.2012.11.002> and Gill & Haned (2013) <doi:10.1016/j.fsigen.2012.08.008>.

r-funsurv 1.0.0
Propagated dependencies: r-reda@0.5.6 r-mfpca@1.3-11 r-matrix@1.7-4 r-mass@7.3-65 r-ggplot2@4.0.1 r-fundata@1.3-9
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/zifangkong/FunSurv
Licenses: Expat
Build system: r
Synopsis: Modeling Time-to-Event Data with Functional Predictors
Description:

This package provides a collection of methods for modeling time-to-event data using both functional and scalar predictors. It implements functional data analysis techniques for estimation and inference, allowing researchers to assess the impact of functional covariates on survival outcomes, including time-to-single event and recurrent event outcomes.

r-fdapde 1.1-21
Propagated dependencies: r-rgl@1.3.31 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-plot3d@1.4.2 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=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-fastglcm 1.0.3
Propagated dependencies: r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r6@2.6.1 r-openimager@1.3.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/mlampros/fastGLCM
Licenses: GPL 3
Build system: r
Synopsis: 'GLCM' Texture Features
Description:

Two Gray Level Co-occurrence Matrix ('GLCM') implementations are included: The first is a fast GLCM feature texture computation based on Python Numpy arrays ('Github Repository, <https://github.com/tzm030329/GLCM>). The second is a fast GLCM RcppArmadillo implementation which is parallelized (using OpenMP') with the option to return all GLCM features at once. For more information, see "Artifact-Free Thin Cloud Removal Using Gans" by Toizumi Takahiro, Zini Simone, Sagi Kazutoshi, Kaneko Eiji, Tsukada Masato, Schettini Raimondo (2019), IEEE International Conference on Image Processing (ICIP), pp. 3596-3600, <doi:10.1109/ICIP.2019.8803652>.

r-filecacher 0.2.9
Propagated dependencies: r-vctrs@0.6.5 r-rlang@1.1.6 r-purrr@1.2.0 r-here@1.0.2 r-glue@1.8.0 r-cachem@1.1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/orgadish/filecacher
Licenses: Expat
Build system: r
Synopsis: File Cacher
Description:

The main functions in this package are with_cache() and cached_read(). The former is a simple way to cache an R object into a file on disk, using cachem'. The latter is a wrapper around any standard read function, but caches both the output and the file list info. If the input file list info hasn't changed, the cache is used; otherwise, the original files are re-read. This can save time if the original operation requires reading from many files, and/or involves lots of processing.

r-fplyr 1.3.0
Propagated dependencies: r-iotools@0.3-5 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/fmarotta/fplyr
Licenses: Expat
Build system: r
Synopsis: Apply Functions to Blocks of Files
Description:

Read and process a large delimited file block by block. A block consists of all the contiguous rows that have the same value in the first field. The result can be returned as a list or a data.table, or even directly printed to an output file.

r-fea 0.0.2
Propagated dependencies: r-sp@2.2-0 r-ptinpoly@2.8 r-mass@7.3-65 r-geosphere@1.5-20 r-geometry@0.5.2
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FEA
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Finite Element Modeling for R
Description:

Finite element modeling of beam structures and 2D geometries using constant strain triangles. Applies material properties and boundary conditions (load and constraint) to generate a finite element model. The model produces stress, strain, and nodal displacements; a heat map is available to demonstrate regions where output variables are high or low. Also provides options for creating a triangular mesh of 2D geometries. Package developed with reference to: Bathe, K. J. (1996). Finite Element Procedures.[ISBN 978-0-9790049-5-7] -- Seshu, P. (2012). Textbook of Finite Element Analysis. [ISBN-978-81-203-2315-5] -- Mustapha, K. B. (2018). Finite Element Computations in Mechanics with R. [ISBN 9781315144474].

r-facebookleadsr 0.1.0
Propagated dependencies: r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://windsor.ai/
Licenses: GPL 3
Build system: r
Synopsis: Get Facebook Leads Ads Data via the 'Windsor.ai' API
Description:

Collect your data on digital marketing campaigns from Facebook Leads Ads using the Windsor.ai API <https://windsor.ai/api-fields/>.

r-fpp2 2.5.1
Propagated dependencies: r-rstudioapi@0.17.1 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-forecast@8.24.0 r-fma@2.5 r-expsmooth@2.3 r-crayon@1.5.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://pkg.robjhyndman.com/fpp2/
Licenses: GPL 3
Build system: r
Synopsis: Data for "Forecasting: Principles and Practice" (2nd Edition)
Description:

All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (2nd ed, 2018) by Rob J Hyndman and George Athanasopoulos <https://otexts.com/fpp2/>. All packages required to run the examples are also loaded.

r-flipscores 1.3.2
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=flipscores
Licenses: GPL 2
Build system: r
Synopsis: Robust Score Testing in GLMs, by Sign-Flip Contributions
Description:

This package provides robust tests for testing in GLMs, by sign-flipping score contributions. The tests are robust against overdispersion, heteroscedasticity and, in some cases, ignored nuisance variables. See Hemerik, Goeman and Finos (2020) <doi:10.1111/rssb.12369>.

r-fdesigns 1.2
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-mvquad@1.0-8 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=fdesigns
Licenses: GPL 2
Build system: r
Synopsis: Optimal Experimental Designs for Dynamic/Functional Models
Description:

Optimal experimental designs for functional linear and functional generalised linear models, for scalar responses and profile/dynamic factors. The designs are optimised using the coordinate exchange algorithm. The methods are discussed by Michaelides (2023) <https://eprints.soton.ac.uk/474982/1/Thesis_DamianosMichaelides_Final_pdfa_1_.pdf>.

r-favr 1.0.0
Propagated dependencies: r-vctrs@0.6.5 r-tidyselect@1.2.1 r-rlang@1.1.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://lj-jenkins.github.io/favr/
Licenses: Expat
Build system: r
Synopsis: Function Argument Validation
Description:

Validate function arguments succinctly with informative error messages and optional automatic type casting and size recycling. Enable schema-based assertions by attaching reusable rules to data.frame and list objects for use throughout workflows.

r-fdapoifd 2.0.1
Propagated dependencies: r-tibble@3.3.0 r-reshape2@1.4.5 r-patchwork@1.3.2 r-magrittr@2.0.4 r-igraph@2.2.1 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/aefdz/fdaPOIFD
Licenses: GPL 3
Build system: r
Synopsis: Partially Observed Integrated Functional Depth
Description:

Integrated Functional Depth for Partially Observed Functional Data and applications to visualization, outlier detection and classification. It implements the methods proposed in: Elà as, A., Jiménez, R., Paganoni, A. M. and Sangalli, L. M., (2023), "Integrated Depth for Partially Observed Functional Data", Journal of Computational and Graphical Statistics, <doi:10.1080/10618600.2022.2070171>. Elà as, A., Jiménez, R., & Shang, H. L. (2023), "Depth-based reconstruction method for incomplete functional data", Computational Statistics, <doi:10.1007/s00180-022-01282-9>. Elà as, A., Nagy, S. (2024), "Statistical properties of partially observed integrated functional depths", TEST, <doi:10.1007/s11749-024-00954-6>.

r-fastkmedoids 1.2
Propagated dependencies: 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=fastkmedoids
Licenses: GPL 2+
Build system: r
Synopsis: Faster K-Medoids Clustering Algorithms: FastPAM, FastCLARA, FastCLARANS
Description:

R wrappers of C++ implementation of Faster K-Medoids clustering algorithms (FastPAM, FastCLARA and FastCLARANS) proposed in Erich Schubert, Peter J. Rousseeuw 2019 <doi:10.1007/978-3-030-32047-8_16>.

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