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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-gensphere 1.3
Propagated dependencies: r-sphericalcubature@1.5 r-simplicialcubature@1.3 r-rgl@1.3.31 r-mvmesh@1.6 r-geometry@0.5.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gensphere
Licenses: GPL 3+
Build system: r
Synopsis: Generalized Spherical Distributions
Description:

Define and compute with generalized spherical distributions - multivariate probability laws that are specified by a star shaped contour (directional behavior) and a radial component. The methods are described in Nolan (2016) <doi:10.1186/s40488-016-0053-0>.

r-gwbr 1.0.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gwbr
Licenses: GPL 3
Build system: r
Synopsis: Local and Global Beta Regression
Description:

Fit a regression model for when the response variable is presented as a ratio or proportion. This adjustment can occur globally, with the same estimate for the entire study space, or locally, where a beta regression model is fitted for each region, considering only influential locations for that area. Da Silva, A. R. and Lima, A. O. (2017) <doi:10.1016/j.spasta.2017.07.011>.

r-ggseg 1.6.8
Dependencies: proj@9.3.1 geos@3.12.1 gdal@3.8.2
Propagated dependencies: r-vctrs@0.6.5 r-tidyr@1.3.1 r-sf@1.0-23 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/ggseg/ggseg
Licenses: Expat
Build system: r
Synopsis: Plotting Tool for Brain Atlases
Description:

This package contains ggplot2 geom for plotting brain atlases using simple features. The largest component of the package is the data for the two built-in atlases. Mowinckel & Vidal-Piñeiro (2020) <doi:10.1177/2515245920928009>.

r-gamclass 0.62.7
Propagated dependencies: r-rpart@4.1.24 r-randomforest@4.7-1.2 r-latticeextra@0.6-31 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/jhmaindonald/gamclass
Licenses: GPL 2+
Build system: r
Synopsis: Functions and Data for a Course on Modern Regression and Classification
Description:

This package provides functions and data are provided that support a course that emphasizes statistical issues of inference and generalizability. The functions are designed to make it straightforward to illustrate the use of cross-validation, the training/test approach, simulation, and model-based estimates of accuracy. Methods considered are Generalized Additive Modeling, Linear and Quadratic Discriminant Analysis, Tree-based methods, and Random Forests.

r-grape 0.1.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GRAPE
Licenses: GPL 2
Build system: r
Synopsis: Gene-Ranking Analysis of Pathway Expression
Description:

Gene-Ranking Analysis of Pathway Expression (GRAPE) is a tool for summarizing the consensus behavior of biological pathways in the form of a template, and for quantifying the extent to which individual samples deviate from the template. GRAPE templates are based only on the relative rankings of the genes within the pathway and can be used for classification of tissue types or disease subtypes. GRAPE can be used to represent gene-expression samples as vectors of pathway scores, where each pathway score indicates the departure from a given collection of reference samples. The resulting pathway- space representation can be used as the feature set for various applications, including survival analysis and drug-response prediction. Users of GRAPE should use the following citation: Klein MI, Stern DF, and Zhao H. GRAPE: A pathway template method to characterize tissue-specific functionality from gene expression profiles. BMC Bioinformatics, 18:317 (June 2017).

r-genderbr 1.2.0
Propagated dependencies: r-purrr@1.2.0 r-jsonlite@2.0.0 r-httr@1.4.7 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/meirelesff/genderBR
Licenses: GPL 2+
Build system: r
Synopsis: Predict Gender from Brazilian First Names
Description:

This package provides a method to predict and report gender from Brazilian first names using the Brazilian Institute of Geography and Statistics Census data.

r-gsd 1.0.0
Propagated dependencies: r-matrix@1.7-4 r-igraph@2.2.1 r-ggplot2@4.0.1 r-ebayesthresh@1.4-12
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GSD
Licenses: GPL 2+
Build system: r
Synopsis: Graph Signal Decomposition
Description:

Graph signals residing on the vertices of a graph have recently gained prominence in research in various fields. Many methodologies have been proposed to analyze graph signals by adapting classical signal processing tools. Recently, several notable graph signal decomposition methods have been proposed, which include graph Fourier decomposition based on graph Fourier transform, graph empirical mode decomposition, and statistical graph empirical mode decomposition. This package efficiently implements multiscale analysis applicable to various fields, and offers an effective tool for visualizing and decomposing graph signals. For the detailed methodology, see Ortega et al. (2018) <doi:10.1109/JPROC.2018.2820126>, Shuman et al. (2013) <doi:10.1109/MSP.2012.2235192>, Tremblay et al. (2014) <https://www.eurasip.org/Proceedings/Eusipco/Eusipco2014/HTML/papers/1569922141.pdf>, and Cho et al. (2024) "Statistical graph empirical mode decomposition by graph denoising and boundary treatment".

r-grabsampling 1.0.0
Propagated dependencies: r-reshape2@1.4.5 r-plyr@1.8.9 r-ggthemes@5.1.0 r-ggplot2@4.0.1 r-extradistr@1.10.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/Mayooran1987/grabsampling
Licenses: GPL 2+
Build system: r
Synopsis: Probability of Detection for Grab Sample Selection
Description:

This package provides functions for obtaining the probability of detection, for grab samples selection by using two different methods such as systematic or random based on two-state Markov chain model. For detection probability calculation, we used results from Bhat, U. and Lal, R. (1988) <doi:10.2307/1427041>.

r-getdteval 0.0.2
Propagated dependencies: r-microbenchmark@1.5.0 r-formulaic@0.0.8 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=getDTeval
Licenses: GPL 3
Build system: r
Synopsis: Translating Coding Statements using get() and eval() for Improved Run-Time Coding Efficiency
Description:

The getDTeval() function facilitates the translation of the original coding statement to an optimized form for improved runtime efficiency without compromising on the programmatic coding design. The function can either provide a translation of the coding statement, directly evaluate the translation to return a coding result, or provide both of these outputs.

r-gater 0.1.16
Propagated dependencies: r-tibble@3.3.0 r-terra@1.8-86 r-spatstat-geom@3.6-1 r-spatialpack@0.4-1 r-sparr@2.3-16 r-rlang@1.1.6 r-lifecycle@1.0.4 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/lance-waller-lab/gateR
Licenses: ASL 2.0
Build system: r
Synopsis: Flow/Mass Cytometry Gating via Spatial Kernel Density Estimation
Description:

Estimates statistically significant marker combination values within which one immunologically distinctive group (i.e., disease case) is more associated than another group (i.e., healthy control), successively, using various combinations (i.e., "gates") of markers to examine features of cells that may be different between groups. For a two-group comparison, the gateR package uses the spatial relative risk function estimated using the sparr package. Details about the sparr package methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.

r-geppe 1.0
Propagated dependencies: r-rfast2@0.1.5.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=geppe
Licenses: GPL 2+
Build system: r
Synopsis: Generalised Exponential Poisson and Poisson Exponential Distributions
Description:

Maximum likelihood estimation, random values generation, density computation and other functions for the exponential-Poisson generalised exponential-Poisson and Poisson-exponential distributions. References include: Rodrigues G. C., Louzada F. and Ramos P. L. (2018). "Poisson-exponential distribution: different methods of estimation". Journal of Applied Statistics, 45(1): 128--144. <doi:10.1080/02664763.2016.1268571>. Louzada F., Ramos, P. L. and Ferreira, H. P. (2020). "Exponential-Poisson distribution: estimation and applications to rainfall and aircraft data with zero occurrence". Communications in Statistics--Simulation and Computation, 49(4): 1024--1043. <doi:10.1080/03610918.2018.1491988>. Barreto-Souza W. and Cribari-Neto F. (2009). "A generalization of the exponential-Poisson distribution". Statistics and Probability Letters, 79(24): 2493--2500. <doi:10.1016/j.spl.2009.09.003>.

r-ggnuplot 0.1.0
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/hriebl/ggnuplot
Licenses: Expat
Build system: r
Synopsis: Make 'ggplot2' Look Like 'gnuplot'
Description:

This package provides a theme, a discrete color palette, and continuous scales to make ggplot2 look like gnuplot'. This may be helpful if you use both ggplot2 and gnuplot in one project.

r-genotriplo 1.1.3
Propagated dependencies: r-tidyr@1.3.1 r-shinythemes@1.2.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-rmixmod@2.1.10 r-rlang@1.1.6 r-processx@3.8.6 r-htmltools@0.5.8.1 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dt@0.34.0 r-dplyr@1.1.4 r-doparallel@1.0.17 r-cowplot@1.2.0
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-gfd 0.3.3
Propagated dependencies: r-tippy@0.1.0 r-shinywidgets@0.9.0 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-plyr@1.8.9 r-plotrix@3.8-13 r-matrix@1.7-4 r-mass@7.3-65 r-magic@1.6-1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GFD
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Tests for General Factorial Designs
Description:

Implemented are the Wald-type statistic, a permuted version thereof as well as the ANOVA-type statistic for general factorial designs, even with non-normal error terms and/or heteroscedastic variances, for crossed designs with an arbitrary number of factors and nested designs with up to three factors. Friedrich et al. (2017) <doi:10.18637/jss.v079.c01>.

r-gephiforr 0.1.1
Propagated dependencies: r-rdpack@2.6.4 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GephiForR
Licenses: Expat
Build system: r
Synopsis: 'Gephi' Network Visualization
Description:

This package implements key features of Gephi for network visualization, including ForceAtlas2 (with LinLog mode), network scaling, and network rotations. It also includes easy network visualization tools such as edge and node color assignment for recreating Gephi'-style graphs in R. The package references layout algorithms developed by Jacomy, M., Venturini T., Heymann S., and Bastian M. (2014) <doi:10.1371/journal.pone.0098679> and Noack, A. (2009) <doi:10.48550/arXiv.0807.4052>.

r-gwalkr 0.2.1
Propagated dependencies: r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-openssl@2.3.4 r-jsonlite@2.0.0 r-htmlwidgets@1.6.4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/Kanaries/GWalkR/
Licenses: FSDG-compatible
Build system: r
Synopsis: Interactive Exploratory Data Analysis Tool
Description:

Simplify your R data analysis and data visualization workflow by turning your data frame into an interactive Tableau'-like interface, leveraging the graphic-walker JavaScript library and the htmlwidgets package.

r-geboes-score 1.0.0
Propagated dependencies: r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://billdenney.github.io/geboes.score/
Licenses: GPL 3+
Build system: r
Synopsis: Evaluate the Geboes Score for Histology in Ulcerative Colitis
Description:

Evaluate and validate the Geboes score for histological assessment of inflammation in ulcerative colitis. The original Geboes score from Geboes, et al. (2000) <doi:10.1136/gut.47.3.404>, binary version from Li, et al. (2019) <doi:10.1093/ecco-jcc/jjz022>, and continuous version from Magro, et al. (2020) <doi:10.1093/ecco-jcc/jjz123> are all described and implemented.

r-grain 1.4.5
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-igraph@2.2.1 r-grbase@2.0.3 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://people.math.aau.dk/~sorenh/software/gR/
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Networks
Description:

Probability propagation in Bayesian networks, also known as graphical independence networks. Documentation of the package is provided in vignettes included in the package and in the paper by Højsgaard (2012, <doi:10.18637/jss.v046.i10>). See citation("gRain") for details.

r-ggtreebar 0.1.0
Propagated dependencies: r-treemapify@2.6.0 r-ggplot2@4.0.1 r-ggfittext@0.10.2 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/hrryt/ggtreebar
Licenses: GPL 3+
Build system: r
Synopsis: Make Treemap Bar Charts with 'ggplot2'
Description:

This package provides ggplot2 geoms analogous to geom_col() and geom_bar() that allow for treemaps using treemapify nested within each bar segment. Also provides geometries for subgroup bordering and text annotation.

r-gvlma 1.0.0.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gvlma
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Global Validation of Linear Models Assumptions
Description:

This package provides methods from the paper: Pena, EA and Slate, EH, "Global Validation of Linear Model Assumptions," J. American Statistical Association, 101(473):341-354, 2006.

r-grshiny 1.0.1
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-sirt@4.2-133 r-shinywidgets@0.9.0 r-shiny@1.11.1 r-sass@0.4.10 r-readr@2.1.6 r-purrr@1.2.0 r-openxlsx@4.2.8.1 r-officer@0.7.1 r-mirt@1.45.1 r-mass@7.3-65 r-magrittr@2.0.4 r-lavaan@0.6-20 r-gt@1.3.0 r-ggplot2@4.0.1 r-flextable@0.9.10 r-dt@0.34.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/sooyongl/GRShiny
Licenses: GPL 3+
Build system: r
Synopsis: Graded Response Model
Description:

Simulation and analysis of graded response data with different types of estimators. Also, an interactive shiny application is provided with graphics for characteristic and information curves. Samejima (2018) <doi:10.1007/978-1-4757-2691-6_5>.

r-gplite 0.13.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gplite
Licenses: GPL 3
Build system: r
Synopsis: General Purpose Gaussian Process Modelling
Description:

This package implements the most common Gaussian process (GP) models using Laplace and expectation propagation (EP) approximations, maximum marginal likelihood (or posterior) inference for the hyperparameters, and sparse approximations for larger datasets.

r-ggplotassist 0.1.3
Propagated dependencies: r-tidyverse@2.0.0 r-tibble@3.3.0 r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinyace@0.4.4 r-shiny@1.11.1 r-scales@1.4.0 r-rstudioapi@0.17.1 r-moonbook@0.3.1 r-miniui@0.1.2 r-magrittr@2.0.4 r-ggthemes@5.1.0 r-ggplot2@4.0.1 r-gcookbook@2.0.1 r-editdata@0.1.8 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/cardiomoon/ggplotAssist
Licenses: GPL 3
Build system: r
Synopsis: 'RStudio' Addin for Teaching and Learning 'ggplot2'
Description:

An RStudio addin for teaching and learning making plot using the ggplot2 package. You can learn each steps of making plot by clicking your mouse without coding. You can get resultant code for the plot.

r-ghypernet 1.1.2
Propagated dependencies: r-texreg@1.39.5 r-rootsolve@1.8.2.4 r-rlang@1.1.6 r-reshape2@1.4.5 r-purrr@1.2.0 r-plyr@1.8.9 r-pbmcapply@1.5.1 r-numbers@0.9-2 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://ghyper.net
Licenses: AGPL 3
Build system: r
Synopsis: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs
Description:

This package provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG). To learn how to use it, check the vignettes for a quick tutorial. Please reference its use as Casiraghi, G., Nanumyan, V. (2019) <doi:10.5281/zenodo.2555300> together with those relevant references from the one listed below. The package is based on the research developed at the Chair of Systems Design, ETH Zurich. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) <doi:10.48550/arXiv.1607.02441>. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) <doi:10.1007/978-3-319-67256-4_11>. Casiraghi, G., (2017) <doi:10.48550/arXiv.1702.02048>. Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) <doi:10.1145/3341161.3342926>. Casiraghi, G. (2019) <doi:10.1007/s41109-019-0241-1>. Casiraghi, G., Nanumyan, V. (2021) <doi:10.1038/s41598-021-92519-y>. Casiraghi, G. (2021) <doi:10.1088/2632-072X/ac0493>.

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