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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-gastempt 0.7.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/dmenne/gastempt
Licenses: GPL 3+
Build system: r
Synopsis: Analyzing Gastric Emptying from MRI or Scintigraphy
Description:

Fits gastric emptying time series from MRI or scintigraphic measurements using nonlinear mixed-model population fits with nlme and Bayesian methods with Stan; computes derived parameters such as t50 and AUC.

r-growthpheno 3.1.18
Propagated dependencies: r-stringi@1.8.7 r-reshape@0.8.10 r-readxl@1.4.5 r-rcolorbrewer@1.1-3 r-jops@0.2.0 r-hmisc@5.2-4 r-ggplot2@4.0.1 r-ggally@2.4.0 r-dplyr@1.1.4 r-dae@3.2.32
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://chris.brien.name/
Licenses: GPL 2+
Build system: r
Synopsis: Functional Analysis of Phenotypic Growth Data to Smooth and Extract Traits
Description:

Assists in the plotting and functional smoothing of traits measured over time and the extraction of features from these traits, implementing the SET (Smoothing and Extraction of Traits) method described in Brien et al. (2020) Plant Methods, 16. Smoothing of growth trends for individual plants using natural cubic smoothing splines or P-splines is available for removing transient effects and segmented smoothing is available to deal with discontinuities in growth trends. There are graphical tools for assessing the adequacy of trait smoothing, both when using this and other packages, such as those that fit nonlinear growth models. A range of per-unit (plant, pot, plot) growth traits or features can be extracted from the data, including single time points, interval growth rates and other growth statistics, such as maximum growth or days to maximum growth. The package also has tools adapted to inputting data from high-throughput phenotyping facilities, such from a Lemna-Tec Scananalyzer 3D (see <https://www.youtube.com/watch?v=MRAF_mAEa7E/> for more information). The package growthPheno can also be installed from <http://chris.brien.name/rpackages/>.

r-geobr 1.9.1
Propagated dependencies: r-sf@1.0-23 r-fs@1.6.6 r-dplyr@1.1.4 r-data-table@1.17.8 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://ipeagit.github.io/geobr/
Licenses: Expat
Build system: r
Synopsis: Download Official Spatial Data Sets of Brazil
Description:

Easy access to official spatial data sets of Brazil as sf objects in R. The package includes a wide range of geospatial data available at various geographic scales and for various years with harmonized attributes, projection and fixed topology.

r-gaupro 0.2.17
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/CollinErickson/GauPro
Licenses: GPL 3
Build system: r
Synopsis: Gaussian Process Fitting
Description:

Fits a Gaussian process model to data. Gaussian processes are commonly used in computer experiments to fit an interpolating model. The model is stored as an R6 object and can be easily updated with new data. There are options to run in parallel, and Rcpp has been used to speed up calculations. For more info about Gaussian process software, see Erickson et al. (2018) <doi:10.1016/j.ejor.2017.10.002>.

r-geogam 0.1-4
Propagated dependencies: r-mgcv@1.9-4 r-mboost@2.9-11 r-mass@7.3-65 r-grpreg@3.5.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=geoGAM
Licenses: GPL 2+
Build system: r
Synopsis: Select Sparse Geoadditive Models for Spatial Prediction
Description:

This package provides a model building procedure to build parsimonious geoadditive model from a large number of covariates. Continuous, binary and ordered categorical responses are supported. The model building is based on component wise gradient boosting with linear effects, smoothing splines and a smooth spatial surface to model spatial autocorrelation. The resulting covariate set after gradient boosting is further reduced through backward elimination and aggregation of factor levels. The package provides a model based bootstrap method to simulate prediction intervals for point predictions. A test data set of a soil mapping case study in Berne (Switzerland) is provided. Nussbaum, M., Walthert, L., Fraefel, M., Greiner, L., and Papritz, A. (2017) <doi:10.5194/soil-3-191-2017>.

r-grader 2.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gradeR
Licenses: Expat
Build system: r
Synopsis: Helps Grade Assignment Submissions in Common R Formats
Description:

After being given the location of your students submissions and a test file, the function runs each file that is an R script, R Markdown file, or Quarto document, and evaluates the results from all the given tests. Results are neatly returned in a data frame that has a row for each student, and a column for each test.

r-gec 0.1.0
Propagated dependencies: r-mistr@0.0.6
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GEC
Licenses: GPL 3
Build system: r
Synopsis: Generalized Exponentiated Composite Distributions
Description:

This package contains the framework of the estimation, sampling, and hypotheses testing for two special distributions (Exponentiated Exponential-Pareto and Exponentiated Inverse Gamma-Pareto) within the family of Generalized Exponentiated Composite distributions. The detailed explanation and the applications of these two distributions were introduced in Bowen Liu, Malwane M.A. Ananda (2022) <doi:10.1080/03610926.2022.2050399>, Bowen Liu, Malwane M.A. Ananda (2022) <doi:10.3390/math10111895>, and Bowen Liu, Malwane M.A. Ananda (2022) <doi:10.3390/app13010645>.

r-gaselect 1.0.25
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/dakep/gaselect
Licenses: GPL 2+
Build system: r
Synopsis: Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data
Description:

This package provides a genetic algorithm for finding variable subsets in high dimensional data with high prediction performance. The genetic algorithm can use ordinary least squares (OLS) regression models or partial least squares (PLS) regression models to evaluate the prediction power of variable subsets. By supporting different cross-validation schemes, the user can fine-tune the tradeoff between speed and quality of the solution.

r-ggenealogy 1.0.3
Propagated dependencies: r-reshape2@1.4.5 r-plyr@1.8.9 r-plotly@4.11.0 r-igraph@2.2.1 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=ggenealogy
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Visualization Tools for Genealogical Data
Description:

This package provides methods for searching through genealogical data and displaying the results. Plotting algorithms assist with data exploration and publication-quality image generation. Includes interactive genealogy visualization tools. Provides parsing and calculation methods for variables in descendant branches of interest. Uses the Grammar of Graphics.

r-genlasso 1.6.1
Propagated dependencies: r-matrix@1.7-4 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/glmgen/genlasso
Licenses: GPL 2+
Build system: r
Synopsis: Path Algorithm for Generalized Lasso Problems
Description:

Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. See Taylor Arnold and Ryan Tibshirani (2016) <doi:10.1080/10618600.2015.1008638>.

r-googletagmanager 0.2.0
Propagated dependencies: r-purrr@1.2.0 r-jsonlite@2.0.0 r-httr@1.4.7 r-googleauthr@2.0.2.1 r-future@1.68.0 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=googleTagManageR
Licenses: Expat
Build system: r
Synopsis: Access the 'Google Tag Manager' API using R
Description:

Interact with the Google Tag Manager API <https://developers.google.com/tag-platform/tag-manager/api/v2>, enabling scripted deployments and updates across multiple tags, triggers, variables and containers.

r-gfdsurv 0.1.1
Propagated dependencies: r-tippy@0.1.0 r-survminer@0.5.1 r-survival@3.8-3 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-plyr@1.8.9 r-mass@7.3-65 r-magic@1.6-1 r-gridextra@2.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/PhilippSteinhauer/GFDsurv
Licenses: GPL 3+
Build system: r
Synopsis: Tests for Survival Data in General Factorial Designs
Description:

Implemented are three Wald-type statistic and respective permuted versions for null hypotheses formulated in terms of cumulative hazard rate functions, medians and the concordance measure, respectively, in the general framework of survival factorial designs with possibly heterogeneous survival and/or censoring distributions, for crossed designs with an arbitrary number of factors and nested designs with up to three factors. Ditzhaus, Dobler and Pauly (2020) <doi:10.1177/0962280220980784> Ditzhaus, Janssen, Pauly (2020) <arXiv: 2004.10818v2> Dobler and Pauly (2019) <doi:10.1177/0962280219831316>.

r-gsheet 0.4.6
Propagated dependencies: r-stringr@1.6.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/maxconway/gsheet
Licenses: GPL 3
Build system: r
Synopsis: Download Google Sheets Using Just the URL
Description:

Simple package to download Google Sheets using just the sharing link. Spreadsheets can be downloaded as a data frame, or as plain text to parse manually. Google Sheets is the new name for Google Docs Spreadsheets <https://www.google.com/sheets/about>.

r-gradlasso 0.1.1
Propagated dependencies: r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/ddefranza/gradLasso
Licenses: Expat
Build system: r
Synopsis: Gradient Descent LASSO with Stability Selection and Bootstrapped Confidence Intervals
Description:

This package implements LASSO regression using gradient descent with support for Gaussian, Binomial, Negative Binomial, and Zero-Inflated Negative Binomial (ZINB) families. Features cross-validation for determining lambda, stability selection, and bootstrapping for confidence intervals. Methods described in Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x> and Meinshausen and Buhlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>.

r-glmxdiag 1.0.0
Propagated dependencies: r-vgam@1.1-13
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=glmxdiag
Licenses: GPL 2+
Build system: r
Synopsis: Collection of Graphic Tools for GLM Diagnostics and some Extensions
Description:

This package provides diagnostic graphic tools for GLMs, beta-binomial regression model (estimated by VGAM package), beta regression model (estimated by betareg package) and negative binomial regression model (estimated by MASS package). Since most of functions implemented in glmxdiag already exist in other packages, the aim is to provide the user unique functions that work on almost all regression models previously specified. Details about some of the implemented functions can be found in Brown (1992) <doi:10.2307/2347617>, Dunn and Smyth (1996) <doi:10.2307/1390802>, O'Hara Hines and Carter (1993) <doi:10.2307/2347405>, Wang (1985) <doi:10.2307/1269708>.

r-ggeasy 0.1.6
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/jonocarroll/ggeasy
Licenses: GPL 2+
Build system: r
Synopsis: Easy Access to 'ggplot2' Commands
Description:

This package provides a series of aliases to commonly used but difficult to remember ggplot2 sequences.

r-groc 1.0.10
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=groc
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Regression on Orthogonal Components
Description:

Robust multiple or multivariate linear regression, nonparametric regression on orthogonal components, classical or robust partial least squares models as described in Bilodeau, Lafaye De Micheaux and Mahdi (2015) <doi:10.18637/jss.v065.i01>.

r-gmdhreg 0.2.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GMDHreg
Licenses: GPL 3
Build system: r
Synopsis: Regression using GMDH Algorithms
Description:

Regression using GMDH algorithms from Prof. Alexey G. Ivakhnenko. Group Method of Data Handling (GMDH), or polynomial neural networks, is a family of inductive algorithms that performs gradually complicated polynomial models and selecting the best solution by an external criterion. In other words, inductive GMDH algorithms give possibility finding automatically interrelations in data, and selecting an optimal structure of model or network. The package includes GMDH Combinatorial, GMDH MIA (Multilayered Iterative Algorithm), GMDH GIA (Generalized Iterative Algorithm) and GMDH Combinatorial with Active Neurons.

r-ggsolvencyii 0.1.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/vanzanden/ggsolvencyii
Licenses: GPL 3
Build system: r
Synopsis: 'ggplot2'-Plot of Composition of Solvency II SCR: SF and IM
Description:

An implementation of ggplot2'-methods to present the composition of Solvency II Solvency Capital Requirement (SCR) as a series of concentric circle-parts. Solvency II (Solvency 2) is European insurance legislation, coming in force by the delegated acts of October 10, 2014. <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ%3AL%3A2015%3A012%3ATOC>. Additional files, defining the structure of the Standard Formula (SF) method of the SCR-calculation are provided. The structure files can be adopted for localization or for insurance companies who use Internal Models (IM). Options are available for combining smaller components, horizontal and vertical scaling, rotation, and plotting only some circle-parts. With outlines and connectors several SCR-compositions can be compared, for example in ORSA-scenarios (Own Risk and Solvency Assessment).

r-gggap 1.0.1
Propagated dependencies: r-ggplot2@4.0.1 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/cmoralesmx/gggap
Licenses: GPL 3
Build system: r
Synopsis: Streamlined Creation of Segments on the Y-Axis of 'ggplot2' Plots
Description:

The function gggap() streamlines the creation of segments on the y-axis of ggplot2 plots which is otherwise not a trivial task to accomplish.

r-geomaroc 0.1.1
Propagated dependencies: r-sf@1.0-23 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/AmineAndam04/R-geomaroc
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Easily Visualize Geographic Data of Morocco
Description:

This package provides tools to easily visualize geographic data of Morocco. This package interacts with data available through the geomarocdata package, which is available in a drat repository. The size of the geomarocdata package is approximately 12 MB.

r-gwpcormapper 0.1.3
Propagated dependencies: r-viridis@0.6.5 r-shinyjs@2.1.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-sf@1.0-23 r-rcpp@1.1.0 r-processx@3.8.6 r-plotly@4.11.0 r-pkgload@1.4.1 r-leaflet@2.2.3 r-htmltools@0.5.8.1 r-golem@0.5.1 r-glue@1.8.0 r-geodist@0.1.1 r-dt@0.34.0 r-dplyr@1.1.4 r-crosstalk@1.2.2 r-corpcor@1.6.10 r-config@0.3.2 r-attempt@0.3.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/gwpcor/gwpcormapper
Licenses: GPL 3
Build system: r
Synopsis: Geographically Weighted Partial Correlation Mapper
Description:

An interactive mapping tool for geographically weighted correlation and partial correlation. Geographically weighted partial correlation coefficients are calculated following (Percival and Tsutsumida, 2017)<doi:10.1553/giscience2017_01_s36> and are described in greater detail in (Tsutsumida et al., 2019)<doi:10.5194/ica-abs-1-372-2019> and (Percival et al., 2021)<arXiv:2101.03491>.

r-genotriplo 1.1.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GenoTriplo
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Genotyping Triploids (or Diploids) from Luminescence Data
Description:

Genotyping of triploid individuals from luminescence data (marker probeset A and B). Works also for diploids. Two main functions: Run_Clustering() that regroups individuals with a same genotype based on proximity and Run_Genotyping() that assigns a genotype to each cluster. For Shiny interface use: launch_GenoShiny().

r-gtestspair 0.1
Propagated dependencies: r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gTestsPair
Licenses: GPL 2+
Build system: r
Synopsis: New Nonparametric Tests for Multivariate Paired Data and Pair Matching
Description:

This package implements three nonparametric two-sample tests for multivariate paired data and pair matching. Methods are described in the associated preprint: <doi:10.48550/arXiv.2007.01497>.

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Total results: 69112