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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-fao56 1.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FAO56
Licenses: GPL 2+
Build system: r
Synopsis: Evapotranspiration Based on FAO Penman-Monteith Equation
Description:

Calculation of Evapotranspiration by FAO Penman-Monteith equation based on Allen, R. G., Pereira, L. S., Raes, D., Smith, M. (1998, ISBN:92-5-104219-5) "Crop evapotranspiration - Guidelines for computing crop water requirements - FAO Irrigation and drainage paper 56".

r-flexurba 0.2.3
Propagated dependencies: r-tidyterra@1.0.0 r-terra@1.8-86 r-sf@1.0-23 r-rcpp@1.1.0 r-nngeo@0.4.8 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-ggspatial@1.1.10 r-ggplot2@4.0.1 r-geos@0.2.4 r-fastmatch@1.1-6 r-exactextractr@0.10.0 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/cvmigero/flexurba
Licenses: Expat
Build system: r
Synopsis: Construct Flexible Urban Delineations
Description:

Enables the construction of flexible urban delineations that can be tailored to specific applications or research questions, see Van Migerode et al. (2024) <DOI:10.1177/23998083241262545> and Van Migerode et al. (2025) <DOI:10.5281/zenodo.15173220>. Originally developed to flexibly reconstruct the Degree of Urbanisation classification of cities, towns and rural areas developed by Dijkstra et al. (2021) <DOI:10.1016/j.jue.2020.103312>. Now it also support a broader range of delineation approaches, using multiple datasets â including population, built-up area, and night-time light grids â and different thresholding methods.

r-forecomp 0.9.0
Propagated dependencies: r-rlang@1.1.6 r-ggplot2@4.0.1 r-forecast@8.24.0 r-astsa@2.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/mcmcs/ForeComp
Licenses: GPL 3+
Build system: r
Synopsis: Size-Power Tradeoff Visualization for Equal Predictive Ability of Two Forecasts
Description:

Offers a set of tools for visualizing and analyzing size and power properties of the test for equal predictive accuracy, the Diebold-Mariano test that is based on heteroskedasticity and autocorrelation-robust (HAR) inference. A typical HAR inference is involved with non-parametric estimation of the long-run variance, and one of its tuning parameters, the truncation parameter, trades off a size and power. Lazarus, Lewis, and Stock (2021)<doi:10.3982/ECTA15404> theoretically characterize the size-power frontier for the Gaussian multivariate location model. ForeComp computes and visualizes the finite-sample size-power frontier of the Diebold-Mariano test based on fixed-b asymptotics together with the Bartlett kernel. To compute the finite-sample size and power, it works with the best approximating ARMA process to the given dataset. It informs the user how their choice of the truncation parameter performs and how robust the testing outcomes are.

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-forested 0.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/simonpcouch/forested
Licenses: Expat
Build system: r
Synopsis: Forest Attributes in U.S. States
Description:

This package provides a small subset of plots throughout the U.S. are sampled and assessed "on-the-ground" as forested or non-forested by the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program, but the FIA also has access to remotely sensed data for all land in the country. The forested package contains data frames intended for use in predictive modeling applications where the more easily-accessible remotely sensed data can be used to predict whether a plot is forested or non-forested. Currently, the package provides data for Washington and Georgia.

r-fdrestimation 1.0.1
Propagated dependencies: r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: <doi:10.12688/f1000research.52999.2>
Licenses: Expat
Build system: r
Synopsis: Estimate, Plot, and Summarize False Discovery Rates
Description:

The user can directly compute and display false discovery rates from inputted p-values or z-scores under a variety of assumptions. p.fdr() computes FDRs, adjusted p-values and decision reject vectors from inputted p-values or z-values. get.pi0() estimates the proportion of data that are truly null. plot.p.fdr() plots the FDRs, adjusted p-values, and the raw p-values points against their rejection threshold lines.

r-footprint 0.2
Propagated dependencies: r-rlang@1.1.6 r-dplyr@1.1.4 r-airportr@0.1.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/acircleda/footprint
Licenses: CC0
Build system: r
Synopsis: Calculate Air Travel Emissions
Description:

This package provides a handy tool to calculate carbon footprints from air travel based on three-letter International Air Transport Association (IATA) airport codes or latitude and longitude. footprint first calculates the great-circle distance between departure and arrival destinations. It then uses the Department of Environment, Food & Rural Affairs (DEFRA) greenhouse gas conversion factors for business air travel to estimate the carbon footprint. These conversion factors consider trip length, flight class (e.g. economy, business), and emissions metric (e.g. carbon dioxide equivalent, methane).

r-fairmodels 1.2.2
Propagated dependencies: r-scales@1.4.0 r-patchwork@1.3.2 r-ggplot2@4.0.1 r-dalex@2.5.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://fairmodels.drwhy.ai/
Licenses: GPL 3
Build system: r
Synopsis: Flexible Tool for Bias Detection, Visualization, and Mitigation
Description:

Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented. Package also supports calculating fairness metrics for regression models. Find more details in (WiÅ niewski, Biecek (2021)) <doi:10.48550/arXiv.2104.00507>.

r-fastvoter 0.0.1
Propagated dependencies: r-rcpp@1.1.0 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://bblodfon.github.io/fastVoteR/
Licenses: LGPL 3+
Build system: r
Synopsis: Efficient Voting Methods for Committee Selection
Description:

This package provides a fast Rcpp'-based implementation of polynomially-computable voting theory methods for committee ranking and scoring. The package includes methods such as Approval Voting (AV), Satisfaction Approval Voting (SAV), sequential Proportional Approval Voting (PAV), and sequential Phragmen's Rule. Weighted variants of these methods are also provided, allowing for differential voter influence.

r-fastaft 1.4
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=fastAFT
Licenses: GPL 2+
Build system: r
Synopsis: Fast Regression for the Accelerated Failure Time (AFT) Model
Description:

Fast censored linear regression for the accelerated failure time (AFT) model of Huang (2013) <doi:10.1111/sjos.12031>.

r-fuzzysim 4.46
Propagated dependencies: r-stringi@1.8.7 r-modeva@3.41
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: http://fuzzysim.r-forge.r-project.org/
Licenses: GPL 3
Build system: r
Synopsis: Fuzzy Similarity in Species Distributions
Description:

This package provides functions to compute fuzzy versions of species occurrence patterns based on presence-absence data (including inverse distance interpolation, trend surface analysis, and prevalence-independent favourability obtained from probability of presence), as well as pair-wise fuzzy similarity (based on fuzzy logic versions of commonly used similarity indices) among those occurrence patterns. Includes also functions for model consensus and comparison (overlap and fuzzy similarity, fuzzy loss, fuzzy gain), and for data preparation, such as obtaining unique abbreviations of species names, defining the background region, cleaning and gridding (thinning) point occurrence data onto raster maps, selecting among (pseudo)absences to address survey bias, converting species lists (long format) to presence-absence tables (wide format), transposing part of a data frame, selecting relevant variables for models, assessing the false discovery rate, or analysing and dealing with multicollinearity. Initially described in Barbosa (2015) <doi:10.1111/2041-210X.12372>.

r-forestly 0.1.3
Propagated dependencies: r-uuid@1.2-1 r-rlang@1.1.6 r-reactr@0.6.1 r-reactable@0.4.5 r-metalite-ae@0.1.3 r-metalite@0.1.4 r-htmltools@0.5.8.1 r-glue@1.8.0 r-ggplot2@4.0.1 r-crosstalk@1.2.2 r-brew@1.0-10
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://merck.github.io/forestly/
Licenses: GPL 3+
Build system: r
Synopsis: Interactive Forest Plot
Description:

Interactive forest plot for clinical trial safety analysis using metalite', reactable', plotly', and Analysis Data Model (ADaM) datasets. Includes functionality for adverse event filtering, incidence-based group filtering, hover-over reveals, and search and sort operations. The workflow allows for metadata construction, data preparation, output formatting, and interactive plot generation.

r-fsm 1.0.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FSM
Licenses: GPL 3
Build system: r
Synopsis: Finite Selection Model
Description:

Randomized and balanced allocation of units to treatment groups using the Finite Selection Model (FSM). The FSM was originally proposed and developed at the RAND corporation by Carl Morris to enhance the experimental design for the now famous Health Insurance Experiment. See Morris (1979) <doi:10.1016/0304-4076(79)90053-8> for details on the original version of the FSM.

r-fauxnaif 0.7.1
Propagated dependencies: 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://fauxnaif.rossellhayes.com/
Licenses: Expat
Build system: r
Synopsis: Convert Values to NA
Description:

This package provides a replacement for dplyr::na_if(). Allows you to specify multiple values to be replaced with NA using a single function.

r-filtro 0.2.0
Propagated dependencies: r-vctrs@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-s7@0.2.1 r-rlang@1.1.6 r-purrr@1.2.0 r-proc@1.19.0.1 r-generics@0.1.4 r-dplyr@1.1.4 r-desirability2@0.2.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/tidymodels/filtro
Licenses: Expat
Build system: r
Synopsis: Feature Selection Using Supervised Filter-Based Methods
Description:

Tidy tools to apply filter-based supervised feature selection methods. These methods score and rank feature relevance using metrics such as p-values, correlation, and importance scores (Kuhn and Johnson (2019) <doi:10.1201/9781315108230>).

r-flir 0.6.0
Propagated dependencies: r-yaml@2.3.10 r-rprojroot@2.1.1 r-git2r@0.36.2 r-fs@1.6.6 r-digest@0.6.39 r-data-table@1.17.8 r-crayon@1.5.3 r-cli@3.6.5 r-astgrepr@0.1.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://flir.etiennebacher.com
Licenses: Expat
Build system: r
Synopsis: Find and Fix Lints in R Code
Description:

Lints are code patterns that are not optimal because they are inefficient, forget corner cases, or are less readable. flir provides a small set of functions to detect those lints and automatically fix them. It builds on astgrepr', which itself uses the Rust crate ast-grep to parse and navigate R code.

r-frailtyhl 2.3
Propagated dependencies: r-survival@3.8-3 r-matrix@1.7-4 r-cmprsk@2.2-12
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=frailtyHL
Licenses: FSDG-compatible
Build system: r
Synopsis: Frailty Models via Hierarchical Likelihood
Description:

This package implements the h-likelihood estimation procedures for general frailty models including competing-risk models and joint models.

r-flexmsm 0.1.2
Propagated dependencies: r-trust@0.1-8 r-mgcv@1.9-4 r-matrixstats@1.5.0 r-gjrm@0.2-6.8
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=flexmsm
Licenses: Expat
Build system: r
Synopsis: General Framework for Flexible Multi-State Survival Modelling
Description:

This package provides a general estimation framework for multi-state Markov processes with flexible specification of the transition intensities. The log-transition intensities can be specified through Generalised Additive Models which allow for virtually any type of covariate effect. Elementary specifications such as time-homogeneous processes and simple parametric forms are also supported. There are no limitations on the type of process one can assume, with both forward and backward transitions allowed and virtually any number of states.

r-fadpclust 1.1.1
Propagated dependencies: r-mfpca@1.3-11 r-fundata@1.3-9 r-fpc@2.2-13 r-fda-usc@2.2.0 r-fda@6.3.0 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=FADPclust
Licenses: GPL 2+
Build system: r
Synopsis: Functional Data Clustering Using Adaptive Density Peak Detection
Description:

An implementation of a clustering algorithm for functional data based on adaptive density peak detection technique, in which the density is estimated by functional k-nearest neighbor density estimation based on a proposed semi-metric between functions. The proposed functional data clustering algorithm is computationally fast since it does not need iterative process. (Alex Rodriguez and Alessandro Laio (2014) <doi:10.1126/science.1242072>; Xiao-Feng Wang and Yifan Xu (2016) <doi:10.1177/0962280215609948>).

r-factorial2x2 0.2.0
Propagated dependencies: r-survival@3.8-3 r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://cran.r-project.org/package=factorial2x2
Licenses: GPL 2
Build system: r
Synopsis: Design and Analysis of a 2x2 Factorial Trial
Description:

Used for the design and analysis of a 2x2 factorial trial for a time-to-event endpoint. It performs power calculations and significance testing as well as providing estimates of the relevant hazard ratios and the corresponding 95% confidence intervals. Important reference papers include Slud EV. (1994) <https://www.ncbi.nlm.nih.gov/pubmed/8086609> Lin DY, Gong J, Gallo P, Bunn PH, Couper D. (2016) <DOI:10.1111/biom.12507> Leifer ES, Troendle JF, Kolecki A, Follmann DA. (2020) <https://github.com/EricSLeifer/factorial2x2/blob/master/Leifer%20et%20al.%20paper.pdf>.

r-fabmix 5.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-mvtnorm@1.3-3 r-mclust@6.1.2 r-mass@7.3-65 r-label-switching@1.8 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-corrplot@0.95 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/mqbssppe/overfittingFABMix
Licenses: GPL 2
Build system: r
Synopsis: Overfitting Bayesian Mixtures of Factor Analyzers with Parsimonious Covariance and Unknown Number of Components
Description:

Model-based clustering of multivariate continuous data using Bayesian mixtures of factor analyzers (Papastamoulis (2019) <DOI:10.1007/s11222-019-09891-z> (2018) <DOI:10.1016/j.csda.2018.03.007>). The number of clusters is estimated using overfitting mixture models (Rousseau and Mengersen (2011) <DOI:10.1111/j.1467-9868.2011.00781.x>): suitable prior assumptions ensure that asymptotically the extra components will have zero posterior weight, therefore, the inference is based on the ``alive components. A Gibbs sampler is implemented in order to (approximately) sample from the posterior distribution of the overfitting mixture. A prior parallel tempering scheme is also available, which allows to run multiple parallel chains with different prior distributions on the mixture weights. These chains run in parallel and can swap states using a Metropolis-Hastings move. Eight different parameterizations give rise to parsimonious representations of the covariance per cluster (following Mc Nicholas and Murphy (2008) <DOI:10.1007/s11222-008-9056-0>). The model parameterization and number of factors is selected according to the Bayesian Information Criterion. Identifiability issues related to label switching are dealt by post-processing the simulated output with the Equivalence Classes Representatives algorithm (Papastamoulis and Iliopoulos (2010) <DOI:10.1198/jcgs.2010.09008>, Papastamoulis (2016) <DOI:10.18637/jss.v069.c01>).

r-fdrci 2.4
Propagated dependencies: 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=fdrci
Licenses: Artistic License 2.0
Build system: r
Synopsis: Permutation-Based FDR Point and Confidence Interval Estimation
Description:

FDR functions for permutation-based estimators, including pi0 as well as FDR confidence intervals. The confidence intervals account for dependencies between tests by the incorporation of an overdispersion parameter, which is estimated from the permuted data. Also included are options for an analog parametric approach.

r-forestr 2.0.2
Propagated dependencies: r-viridis@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-plyr@1.8.9 r-moments@0.14.1 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://github.com/atkinsjeff/forestr
Licenses: GPL 3
Build system: r
Synopsis: Ecosystem and Canopy Structural Complexity Metrics from LiDAR
Description:

This package provides a toolkit for calculating forest and canopy structural complexity metrics from terrestrial LiDAR (light detection and ranging). References: Atkins et al. 2018 <doi:10.1111/2041-210X.13061>; Hardiman et al. 2013 <doi:10.3390/f4030537>; Parker et al. 2004 <doi:10.1111/j.0021-8901.2004.00925.x>.

r-factory 0.1.0
Propagated dependencies: r-rlang@1.1.6 r-purrr@1.2.0
Channel: guix-cran
Location: guix-cran/packages/f.scm (guix-cran packages f)
Home page: https://github.com/jonthegeek/factory
Licenses: Expat
Build system: r
Synopsis: Build Function Factories
Description:

Function factories are functions that make functions. They can be confusing to construct. Straightforward techniques can produce functions that are fragile or hard to understand. While more robust techniques exist to construct function factories, those techniques can be confusing. This package is designed to make it easier to construct function factories.

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