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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-shinyrecipes 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-sortable@0.6.0 r-shinywidgets@0.9.0 r-shinyglide@0.1.4 r-shiny@1.11.1 r-rstudioapi@0.17.1 r-recipes@1.3.1 r-purrr@1.2.0 r-miniui@0.1.2 r-esquisse@2.1.0 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/AlbertoAlmuinha/shinyrecipes
Licenses: GPL 3
Build system: r
Synopsis: Gadget to Use the Data Preprocessing 'recipes' Package Interactively
Description:

This gadget allows you to use the recipes package belonging to tidymodels to carry out the data preprocessing tasks in an interactive way. Build your recipe by dragging the variables, visually analyze your data to decide which steps to use, add those steps and preprocess your data.

r-sfc 0.1.1
Propagated dependencies: r-zoo@1.8-14 r-triangle@1.0 r-tidyr@1.3.1 r-sna@2.8 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ctfysh/sfc
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Substance Flow Computation
Description:

This package provides a function sfc() to compute the substance flow with the input files --- "data" and "model". If sample.size is set more than 1, uncertainty analysis will be executed while the distributions and parameters are supplied in the file "data".

r-sps 0.6.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://marberts.github.io/sps/
Licenses: Expat
Build system: r
Synopsis: Sequential Poisson Sampling
Description:

Sequential Poisson sampling is a variation of Poisson sampling for drawing probability-proportional-to-size samples with a given number of units, and is commonly used for price-index surveys. This package gives functions to draw stratified sequential Poisson samples according to the method by Ohlsson (1998, ISSN:0282-423X), as well as other order sample designs by Rosén (1997, <doi:10.1016/S0378-3758(96)00186-3>), and generate approximate bootstrap replicate weights according to the generalized bootstrap method by Beaumont and Patak (2012, <doi:10.1111/j.1751-5823.2011.00166.x>).

r-support-bws3 0.2-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=support.BWS3
Licenses: GPL 2+
Build system: r
Synopsis: Tools for Case 3 Best-Worst Scaling
Description:

This package provides basic functions that support an implementation of multi-profile case (Case 3) best-worst scaling (BWS). Case 3 BWS is a question-based survey method to elicit people's preferences for attribute levels. Case 3 BWS constructs various combinations of attribute levels (profiles) and then asks respondents to select the best and worst profiles in each choice set. A main function creates a dataset for the analysis from the choice sets and the responses to the questions. For details on Case 3 BWS, refer to Louviere et al. (2015) <doi:10.1017/CBO9781107337855>.

r-spatialvs 1.1
Propagated dependencies: r-nlme@3.1-168 r-mass@7.3-65 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SpatialVS
Licenses: GPL 2
Build system: r
Synopsis: Spatial Variable Selection
Description:

Perform variable selection for the spatial Poisson regression model under the adaptive elastic net penalty. Spatial count data with covariates is the input. We use a spatial Poisson regression model to link the spatial counts and covariates. For maximization of the likelihood under adaptive elastic net penalty, we implemented the penalized quasi-likelihood (PQL) and the approximate penalized loglikelihood (APL) methods. The proposed methods can automatically select important covariates, while adjusting for possible spatial correlations among the responses. More details are available in Xie et al. (2018, <arXiv:1809.06418>). The package also contains the Lyme disease dataset, which consists of the disease case data from 2006 to 2011, and demographic data and land cover data in Virginia. The Lyme disease case data were collected by the Virginia Department of Health. The demographic data (e.g., population density, median income, and average age) are from the 2010 census. Land cover data were obtained from the Multi-Resolution Land Cover Consortium for 2006.

r-siqr 0.8.1
Propagated dependencies: r-quantreg@6.1 r-kernsmooth@2.23-26
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=siqr
Licenses: GPL 3
Build system: r
Synopsis: An R Package for Single-Index Quantile Regression
Description:

Single-Index Quantile Regression is effective in some scenarios. We provides functions that allow users to fit Single-Index Quantile Regression model. It also provides functions to do prediction, estimate standard errors of the single-index coefficients via bootstrap, and visualize the estimated univariate function. Please see W., Y., Y. (2010) <doi:10.1016/j.jmva.2010.02.003> for details.

r-springsteen 0.1.0
Propagated dependencies: r-rlang@1.1.6 r-devtools@2.4.6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/obrienjoey/spRingsteen
Licenses: CC0
Build system: r
Synopsis: All Things Data and Springsteen
Description:

An R data package containing setlists from all Bruce Springsteen concerts over 1973-2021. Also includes all his song details such as lyrics and albums. Data extracted from: <http://brucebase.wikidot.com/>.

r-solar 0.47
Propagated dependencies: r-zoo@1.8-14 r-rcolorbrewer@1.1-3 r-latticeextra@0.6-31 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://oscarperpinan.codeberg.page/solar/
Licenses: GPL 3
Build system: r
Synopsis: Radiation and Photovoltaic Systems
Description:

Calculation methods of solar radiation and performance of photovoltaic systems from daily and intradaily irradiation data sources.

r-stops 1.9-1
Propagated dependencies: r-vegan@2.7-2 r-tgp@2.4-23 r-smacofx@1.22-0 r-smacof@2.1-7 r-scagnostics@0.2-6 r-registry@0.5-1 r-pso@1.0.4 r-pomp@6.4 r-nloptr@2.2.1 r-minerva@1.5.10 r-energy@1.7-12 r-dfoptim@2023.1.0 r-cordillera@1.0-3 r-cmaes@1.0-12 r-clue@0.3-66 r-acepack@1.6.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://r-forge.r-project.org/projects/stops/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Structure Optimized Proximity Scaling
Description:

This package provides methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,<doi:10.1007/s11222-022-10197-w>). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling powers of dissimilarities and configuration distances, Sammon mapping powers of dissimilarities and configuration distances, power stress MDS (POST-MDS), approximate power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling and (power) multidimensional distance analysis (experimental models from smacofx influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters based on goodness-of-fit fit only (i.e., no structure considerations). The package further contains functions for optimization, specifically the adaptive Luus-Jaakola algorithm and a wrapper for Bayesian optimization with treed Gaussian process with jumps to linear models, and functions for various c-structuredness indices. Hyperparameter optimization can be done with a number of techniques but we recommend either Bayesian optimization or particle swarm. For using "Kriging", users need to install a version of the archived DiceOptim R package.

r-stylo 0.7.5
Propagated dependencies: r-tsne@0.1-3.1 r-tcltk2@1.6.1 r-pamr@1.57 r-lattice@0.22-7 r-e1071@1.7-16 r-class@7.3-23 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/computationalstylistics/stylo
Licenses: GPL 3+
Build system: r
Synopsis: Stylometric Multivariate Analyses
Description:

Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.

r-soilassessment 0.3.0
Propagated dependencies: r-terra@1.8-86 r-sp@2.2-0 r-soiltexture@1.5.3 r-sf@1.0-23 r-raster@3.6-32 r-randomforest@4.7-1.2 r-png@0.1-8 r-nnet@7.3-20 r-hmisc@5.2-4 r-googledrive@2.1.2 r-fuzzyahp@0.9.5 r-e1071@1.7-16 r-desolve@1.40 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=soilassessment
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Soil Health Assessment Models for Assessing Soil Conditions and Suitability
Description:

Soil health assessment builds information to improve decision in soil management. It facilitates assessment of soil conditions for crop suitability [such as those given by FAO <https://www.fao.org/land-water/databases-and-software/crop-information/en/>], groundwater recharge, fertility, erosion, salinization [<doi:10.1002/ldr.4211>], carbon sequestration, irrigation potential, and status of soil resources.

r-srda 1.0.0
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 r-foreach@1.5.2 r-elasticnet@1.3 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sRDA
Licenses: Expat
Build system: r
Synopsis: Sparse Redundancy Analysis
Description:

Sparse redundancy analysis for high dimensional (biomedical) data. Directional multivariate analysis to express the maximum variance in the predicted data set by a linear combination of variables of the predictive data set. Implemented in a partial least squares framework, for more details see Csala et al. (2017) <doi:10.1093/bioinformatics/btx374>.

r-sodavis 1.2
Propagated dependencies: r-nnet@7.3-20 r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sodavis
Licenses: GPL 2
Build system: r
Synopsis: SODA: Main and Interaction Effects Selection for Logistic Regression, Quadratic Discriminant and General Index Models
Description:

Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under logistic regression and quadratic discriminant analysis. We also provide an extension, S-SODA, for dealing with the variable selection problem for semi-parametric models with continuous responses.

r-squash 1.0.9
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/aroneklund/squash
Licenses: Artistic License 2.0
Build system: r
Synopsis: Color-Based Plots for Multivariate Visualization
Description:

This package provides functions for color-based visualization of multivariate data, i.e. colorgrams or heatmaps. Lower-level functions map numeric values to colors, display a matrix as an array of colors, and draw color keys. Higher-level plotting functions generate a bivariate histogram, a dendrogram aligned with a color-coded matrix, a triangular distance matrix, and more.

r-skewunit 1.0
Propagated dependencies: r-pracma@2.4.6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=skewunit
Licenses: GPL 2+
Build system: r
Synopsis: Estimation and Other Tools for Skew-Unit Models
Description:

Provide estimation and data generation tools for the skew-unit family discussed based on Mukhopadhyay and Brani (1995) <doi:10.2307/2348710>. The family contains extensions for popular distributions such as the ArcSin discussed in Arnold and Groeneveld (1980) <doi:10.1080/01621459.1980.10477449>, triangular, U-quadratic and Johnson-SB proposed in Cortina-Borja (2006) <doi:10.1111/j.1467-985X.2006.00446_12.x> distributions, among others.

r-sinaplot 1.1.0
Propagated dependencies: r-plyr@1.8.9
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sinaplot
Licenses: GPL 2+
Build system: r
Synopsis: An Enhanced Chart for Simple and Truthful Representation of Single Observations over Multiple Classes
Description:

The sinaplot is a data visualization chart suitable for plotting any single variable in a multiclass data set. It is an enhanced jitter strip chart, where the width of the jitter is controlled by the density distribution of the data within each class.

r-starts 1.3-8
Propagated dependencies: r-sirt@4.2-133 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lam@0.7-22 r-cdm@8.3-14
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/alexanderrobitzsch/STARTS
Licenses: GPL 2+
Build system: r
Synopsis: Functions for the STARTS Model
Description:

This package contains functions for estimating the STARTS model of Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>, <DOI:10.1037/10409-008>. Penalized maximum likelihood estimation and Markov Chain Monte Carlo estimation are also provided, see Luedtke, Robitzsch and Wagner (2018) <DOI:10.1037/met0000155>.

r-simsl 0.2.1
Propagated dependencies: r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=simsl
Licenses: GPL 3
Build system: r
Synopsis: Single-Index Models with a Surface-Link
Description:

An implementation of a single-index regression for optimizing individualized dose rules from an observational study. To model interaction effects between baseline covariates and a treatment variable defined on a continuum, we employ two-dimensional penalized spline regression on an index-treatment domain, where the index is defined as a linear combination of the covariates (a single-index). An unspecified main effect for the covariates is allowed, which can also be modeled through a parametric model. A unique contribution of this work is in the parsimonious single-index parametrization specifically defined for the interaction effect term. We refer to Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1111/biom.13320> (for the case of a discrete treatment) and Park, Petkova, Tarpey, and Ogden (2021) "A single-index model with a surface-link for optimizing individualized dose rules" <arXiv:2006.00267v2> for detail of the method. The model can take a member of the exponential family as a response variable and can also take an ordinal categorical response. The main function of this package is simsl().

r-stmr 0.1.7
Propagated dependencies: r-tidyr@1.3.1 r-quantreg@6.1 r-nlme@3.1-168 r-minpack-lm@1.2-4 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-ggfittext@0.10.2 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://mladenjovanovic.github.io/STMr/
Licenses: Expat
Build system: r
Synopsis: Strength Training Manual R-Language Functions
Description:

Strength training prescription using percent-based approach requires numerous computations and assumptions. STMr package allow users to estimate individual reps-max relationships, implement various progression tables, and create numerous set and rep schemes. The STMr package is originally created as a tool to help writing JovanoviÄ M. (2020) Strength Training Manual <ISBN:979-8604459898>.

r-sportyr 2.2.3
Dependencies: pandoc@2.19.2 pandoc@2.19.2
Propagated dependencies: r-rlang@1.1.6 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggfittext@0.10.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://sportyr.sportsdataverse.org/
Licenses: GPL 3+
Build system: r
Synopsis: Plot Scaled 'ggplot' Representations of Sports Playing Surfaces
Description:

Create scaled ggplot representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.

r-shinyxypad 0.2.0
Propagated dependencies: r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/stla/shinyXYpad
Licenses: GPL 3
Build system: r
Synopsis: XY Controller for 'Shiny'
Description:

This package provides an XY pad input for the Shiny framework. An XY pad is like a bivariate slider. It allows to pick up a pair of numbers.

r-seasepi 0.0.3
Propagated dependencies: r-ngspatial@1.2-2 r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SeasEpi
Licenses: Expat
Build system: r
Synopsis: Spatiotemporal Modeling of Seasonal Infectious Disease
Description:

Spatiotemporal individual-level model of seasonal infectious disease transmission within the Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) framework are applied to model seasonal infectious disease transmission. This package employs a likelihood based Monte Carlo Expectation Conditional Maximization (MCECM) algorithm for estimating model parameters. In addition to model fitting and parameter estimation, the package offers functions for calculating AIC using real pandemic data and conducting simulation studies customized to user-specified model configurations.

r-slim 0.1.1
Propagated dependencies: r-mass@7.3-65 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=slim
Licenses: GPL 3
Build system: r
Synopsis: Singular Linear Models for Longitudinal Data
Description:

Fits singular linear models to longitudinal data. Singular linear models are useful when the number, or timing, of longitudinal observations may be informative about the observations themselves. They are described in Farewell (2010) <doi:10.1093/biomet/asp068>, and are extensions of the linear increments model <doi:10.1111/j.1467-9876.2007.00590.x> to general longitudinal data.

r-starvars 1.1.11
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-vars@1.6-1 r-quantmod@0.4.28 r-optimparallel@1.0-2 r-matrixcalc@1.0-6 r-mass@7.3-65 r-lessr@4.5.1 r-ks@1.15.1 r-foreach@1.5.2 r-dosnow@1.0.20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/andbucci/starvars
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Vector Logistic Smooth Transition Models Estimation and Prediction
Description:

Allows the user to estimate a vector logistic smooth transition autoregressive model via maximum log-likelihood or nonlinear least squares. It further permits to test for linearity in the multivariate framework against a vector logistic smooth transition autoregressive model with a single transition variable. The estimation method is discussed in Terasvirta and Yang (2014, <doi:10.1108/S0731-9053(2013)0000031008>). Also, realized covariances can be constructed from stock market prices or returns, as explained in Andersen et al. (2001, <doi:10.1016/S0304-405X(01)00055-1>).

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