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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-smartsizer 1.0.3
Propagated dependencies: 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=smartsizer
Licenses: GPL 3
Build system: r
Synopsis: Power Analysis for a SMART Design
Description:

This package provides a set of tools for determining the necessary sample size in order to identify the optimal dynamic treatment regime in a sequential, multiple assignment, randomized trial (SMART). Utilizes multiple comparisons with the best methodology to adjust for multiple comparisons. Designed for an arbitrary SMART design. Please see Artman (2018) <doi:10.1093/biostatistics/kxy064> for more details.

r-siren 1.0.6
Propagated dependencies: r-psych@2.5.6 r-lavaan@0.6-20 r-efa-mrfa@1.1.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=siren
Licenses: GPL 3
Build system: r
Synopsis: Hybrid FA-CFA for Controlling Acquiescence in Restricted Factorial Solutions
Description:

This package performs hybrid multi-stage factor analytic procedure for controlling acquiescence in restricted solutions (Ferrando & Lorenzo-Seva, 2000 <https://www.uv.es/revispsi/articulos3.00/ferran7.pdf>).

r-sapo 0.8.0
Dependencies: proj@9.3.1 geos@3.12.1 gdal@3.8.2
Propagated dependencies: r-sf@1.0-23
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/lcgodoy/sapo/
Licenses: GPL 3+
Build system: r
Synopsis: Spatial Association of Different Types of Polygon
Description:

In ecology, spatial data is often represented using polygons. These polygons can represent a variety of spatial entities, such as ecological patches, animal home ranges, or gaps in the forest canopy. Researchers often need to determine if two spatial processes, represented by these polygons, are independent of each other. For instance, they might want to test if the home range of a particular animal species is influenced by the presence of a certain type of vegetation. To address this, Godoy et al. (2022) (<doi:10.1016/j.spasta.2022.100695>) developed conditional Monte Carlo tests. These tests are designed to assess spatial independence while taking into account the shape and size of the polygons.

r-smbinning 0.9
Propagated dependencies: r-sqldf@0.4-11 r-partykit@1.2-24 r-gsubfn@0.7 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=smbinning
Licenses: GPL 2+
Build system: r
Synopsis: Scoring Modeling and Optimal Binning
Description:

This package provides a set of functions to build a scoring model from beginning to end, leading the user to follow an efficient and organized development process, reducing significantly the time spent on data exploration, variable selection, feature engineering, binning and model selection among other recurrent tasks. The package also incorporates monotonic and customized binning, scaling capabilities that transforms logistic coefficients into points for a better business understanding and calculates and visualizes classic performance metrics of a classification model.

r-spongebob 0.4.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jayqi/spongebob
Licenses: Modified BSD
Build system: r
Synopsis: SpongeBob-Case Converter : spOngEboB-CASe CoNVertER
Description:

Convert text (and text in R objects) to Mocking SpongeBob case <https://knowyourmeme.com/memes/mocking-spongebob> and show them off in fun ways. CoNVErT TexT (AnD TeXt In r ObJeCtS) To MOCkINg SpoNgebOb CAsE <https://knowyourmeme.com/memes/mocking-spongebob> aND shOw tHem OFf IN Fun WayS.

r-sbic 0.2.0
Propagated dependencies: r-rcpp@1.1.0 r-r-oo@1.27.1 r-r-methodss3@1.8.2 r-polca@1.6.0.2 r-mclust@6.1.2 r-igraph@2.2.1 r-hash@2.2.6.3 r-flexmix@2.3-20 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Lucaweihs/sBIC
Licenses: GPL 3+
Build system: r
Synopsis: Computing the Singular BIC for Multiple Models
Description:

Computes the sBIC for various singular model collections including: binomial mixtures, factor analysis models, Gaussian mixtures, latent forests, latent class analyses, and reduced rank regressions.

r-smr 2.1.0
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://bendeivide.github.io/SMR/
Licenses: GPL 2+
Build system: r
Synopsis: Externally Studentized Midrange Distribution
Description:

Computes the studentized midrange distribution (pdf, cdf and quantile) and generates random numbers.

r-simmer 4.4.7
Propagated dependencies: r-rcpp@1.1.0 r-magrittr@2.0.4 r-codetools@0.2-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://r-simmer.org
Licenses: GPL 2+
Build system: r
Synopsis: Discrete-Event Simulation for R
Description:

This package provides a process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in C++ with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type. Documentation about simmer is provided by several vignettes included in this package, via the paper by Ucar, Smeets & Azcorra (2019, <doi:10.18637/jss.v090.i02>), and the paper by Ucar, Hernández, Serrano & Azcorra (2018, <doi:10.1109/MCOM.2018.1700960>); see citation("simmer") for details.

r-shinychatr 1.2.0
Propagated dependencies: r-shiny@1.11.1 r-r6@2.6.1 r-purrr@1.2.0 r-dbi@1.2.3 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/julianschmocker/shinyChatR
Licenses: GPL 3+
Build system: r
Synopsis: R Shiny Chat Module
Description:

This package provides an easy-to-use module for adding a chat to a Shiny app. Allows users to send messages and view messages from other users. Messages can be stored in a database or a .rds file.

r-sbsdiff 0.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SBSDiff
Licenses: Expat
Build system: r
Synopsis: Satorra-Bentler Scaled Chi-Squared Difference Test
Description:

Calculates a Satorra-Bentler scaled chi-squared difference test between nested models that were estimated using maximum likelihood (ML) with robust standard errors, which cannot be calculated the traditional way. For details see Satorra & Bentler (2001) <doi:10.1007/bf02296192> and Satorra & Bentler (2010) <doi:10.1007/s11336-009-9135-y>. This package may be particularly helpful when used in conjunction with Mplus software, specifically when implementing the complex survey option. In such cases, the model estimator in Mplus defaults to ML with robust standard errors.

r-sfarrow 0.4.1
Propagated dependencies: r-sf@1.0-23 r-jsonlite@2.0.0 r-dplyr@1.1.4 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/wcjochem/sfarrow
Licenses: Expat
Build system: r
Synopsis: Read/Write Simple Feature Objects ('sf') with 'Apache' 'Arrow'
Description:

Support for reading/writing simple feature ('sf') spatial objects from/to Parquet files. Parquet files are an open-source, column-oriented data storage format from Apache (<https://parquet.apache.org/>), now popular across programming languages. This implementation converts simple feature list geometries into well-known binary format for use by arrow', and coordinate reference system information is maintained in a standard metadata format.

r-sbmtrees 1.4
Propagated dependencies: r-sn@2.1.1 r-rcppprogress@0.4.2 r-rcppdist@0.1.1.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pg@0.2.4 r-nnet@7.3-20 r-mvtnorm@1.3-3 r-mice@3.18.0 r-matrix@1.7-4 r-mass@7.3-65 r-lme4@1.1-37 r-dplyr@1.1.4 r-arm@1.14-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SBMTrees
Licenses: GPL 2
Build system: r
Synopsis: Longitudinal Sequential Imputation and Prediction with Bayesian Trees Mixed-Effects Models for Longitudinal Data
Description:

This package implements a sequential imputation framework using Bayesian Mixed-Effects Trees ('SBMTrees') for handling missing data in longitudinal studies. The package supports a variety of models, including non-linear relationships and non-normal random effects and residuals, leveraging Dirichlet Process priors for increased flexibility. Key features include handling Missing at Random (MAR) longitudinal data, imputation of both covariates and outcomes, and generating posterior predictive samples for further analysis. The methodology is designed for applications in epidemiology, biostatistics, and other fields requiring robust handling of missing data in longitudinal settings.

r-sbdecomp 1.2
Propagated dependencies: r-twang@2.6.2 r-survey@4.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SBdecomp
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Estimation of the Proportion of SB Explained by Confounders
Description:

Uses parametric and nonparametric methods to quantify the proportion of the estimated selection bias (SB) explained by each observed confounder when estimating propensity score weighted treatment effects. Parast, L and Griffin, BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal Treatment Effect Estimates". Statistics in Medicine, 39(18): 2447- 2476 <doi: 10.1002/sim.8549>.

r-stableestim 2.4
Propagated dependencies: r-stabledist@0.7-2 r-rdpack@2.6.4 r-numderiv@2016.8-1.1 r-mass@7.3-65 r-fbasics@4041.97
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://geobosh.github.io/StableEstim/
Licenses: GPL 2+
Build system: r
Synopsis: Estimate the Four Parameters of Stable Laws using Different Methods
Description:

Estimate the four parameters of stable laws using maximum likelihood method, generalised method of moments with finite and continuum number of points, iterative Koutrouvelis regression and Kogon-McCulloch method. The asymptotic properties of the estimators (covariance matrix, confidence intervals) are also provided.

r-statebins 1.4.0
Propagated dependencies: r-scales@1.4.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://gitlab.com/hrbrmstr/statebins
Licenses: Expat
Build system: r
Synopsis: Create United States Uniform Cartogram Heatmaps
Description:

The cartogram heatmaps generated by the included methods are an alternative to choropleth maps for the United States and are based on work by the Washington Post graphics department in their report on "The states most threatened by trade" (<http://www.washingtonpost.com/wp-srv/special/business/states-most-threatened-by-trade/>). "State bins" preserve as much of the geographic placement of the states as possible but have the look and feel of a traditional heatmap. Functions are provided that allow for use of a binned, discrete scale, a continuous scale or manually specified colors depending on what is needed for the underlying data.

r-sits 1.5.4
Propagated dependencies: r-yaml@2.3.10 r-units@1.0-0 r-torch@0.16.3 r-tmap@4.2 r-tidyr@1.3.1 r-tibble@3.3.0 r-terra@1.8-86 r-slider@0.3.3 r-sf@1.0-23 r-rstac@1.0.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-randomforest@4.7-1.2 r-purrr@1.2.0 r-luz@0.5.1 r-lubridate@1.9.4 r-leaflet@2.2.3 r-leafgl@0.2.2 r-httr2@1.2.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/e-sensing/sits/
Licenses: GPL 2
Build system: r
Synopsis: Satellite Image Time Series Analysis for Earth Observation Data Cubes
Description:

An end-to-end toolkit for land use and land cover classification using big Earth observation data. Builds satellite image data cubes from cloud collections. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Enables merging of multi-source imagery (SAR, optical, DEM). Includes functions for quality assessment of training samples using self-organized maps and to reduce training samples imbalance. Provides machine learning algorithms including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolution neural networks, and temporal attention encoders. Performs efficient classification of big Earth observation data cubes and includes functions for post-classification smoothing based on Bayesian inference. Enables best practices for estimating area and assessing accuracy of land change. Includes object-based spatio-temporal segmentation for space-time OBIA. Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.

r-svyvarsel 1.0.1
Propagated dependencies: r-survey@4.4-8 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=svyVarSel
Licenses: GPL 3+
Build system: r
Synopsis: Variable Selection for Complex Survey Data
Description:

Fit design-based linear and logistic elastic nets with complex survey data considering the sampling design when defining training and test sets using replicate weights. Methods implemented in this package are described in: A. Iparragirre, T. Lumley, I. Barrio, I. Arostegui (2024) <doi:10.1002/sta4.578>.

r-support-bws2 0.4-0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=support.BWS2
Licenses: GPL 2+
Build system: r
Synopsis: Tools for Case 2 Best-Worst Scaling
Description:

This package provides three basic functions that support an implementation of Case 2 (profile case) best-worst scaling. The first is to convert an orthogonal main-effect design into questions, the second is to create a dataset suitable for analysis, and the third is to calculate count-based scores. For details, see Aizaki and Fogarty (2019) <doi:10.1016/j.jocm.2019.100171>.

r-sanple 0.2.0
Propagated dependencies: r-scales@1.4.0 r-salso@0.3.57 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/laura-dangelo/SANple
Licenses: Expat
Build system: r
Synopsis: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo
Description:

Estimate Bayesian nested mixture models via Markov Chain Monte Carlo methods. Specifically, the package implements the common atoms model (Denti et al., 2023), and hybrid finite-infinite models. All models use Gaussian mixtures with a normal-inverse-gamma prior distribution on the parameters. Additional functions are provided to help analyzing the results of the fitting procedure. References: Denti, Camerlenghi, Guindani, Mira (2023) <doi:10.1080/01621459.2021.1933499>, Dâ Angelo, Denti (2024) <doi:10.1214/24-BA1458>.

r-sccca 0.1.1
Propagated dependencies: r-seurat@5.3.1 r-scales@1.4.0 r-plyr@1.8.9 r-openxlsx@4.2.8.1 r-hgnchelper@0.8.15 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sccca
Licenses: GPL 3+
Build system: r
Synopsis: Single-Cell Correlation Based Cell Type Annotation
Description:

Performing cell type annotation based on cell markers from a unified database. The approach utilizes correlation-based approach combined with association analysis using Fisher-exact and phyper statistical tests (Upton, Graham JG. (1992) <DOI:10.2307/2982890>).

r-sumsome 1.1.0
Propagated dependencies: r-rnifti@1.8.0 r-rcpp@1.1.0 r-pari@1.1.3 r-aribrain@0.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/annavesely/sumSome
Licenses: GPL 2+
Build system: r
Synopsis: Permutation True Discovery Guarantee by Sum-Based Tests
Description:

It allows to quickly perform permutation-based closed testing by sum-based global tests, and construct lower confidence bounds for the TDP, simultaneously over all subsets of hypotheses. As a main feature, it produces simultaneous lower confidence bounds for the proportion of active voxels in different clusters for fMRI cluster analysis. Details may be found in Vesely, Finos, and Goeman (2020) <arXiv:2102.11759>.

r-snpannotator 1.4.6
Propagated dependencies: r-xml2@1.5.0 r-rmarkdown@2.30 r-readr@2.1.6 r-progress@1.2.3 r-png@0.1-8 r-openxlsx@4.2.8.1 r-logger@0.4.1 r-kableextra@1.4.0 r-jsonlite@2.0.0 r-ini@0.3.1 r-igraph@2.2.1 r-httr@1.4.7 r-ggraph@2.2.2 r-ggplot2@4.0.1 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=SNPannotator
Licenses: GPL 3
Build system: r
Synopsis: Automated Functional Annotation of Genetic Variants and Linked Proxies
Description:

To automated functional annotation of genetic variants and linked proxies. Linked SNPs in moderate to high linkage disequilibrium (e.g. r2>0.50) with the corresponding index SNPs will be selected for further analysis.

r-sparkhail 0.1.1
Propagated dependencies: r-sparklyr-nested@0.0.4 r-sparklyr@1.9.3 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sparkhail
Licenses: ASL 2.0 FSDG-compatible
Build system: r
Synopsis: 'Sparklyr' Extension for 'Hail'
Description:

Hail is an open-source, general-purpose, python based data analysis tool with additional data types and methods for working with genomic data, see <https://hail.is/>. Hail is built to scale and has first-class support for multi-dimensional structured data, like the genomic data in a genome-wide association study (GWAS). Hail is exposed as a python library, using primitives for distributed queries and linear algebra implemented in scala', spark', and increasingly C++'. The sparkhail is an R extension using sparklyr package. The idea is to help R users to use hail functionalities with the well-know tidyverse syntax, see <https://www.tidyverse.org/>.

r-smotefamily 1.4.0
Propagated dependencies: r-igraph@2.2.1 r-fnn@1.1.4.1 r-dbscan@1.2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=smotefamily
Licenses: GPL 3+
Build system: r
Synopsis: Collection of Oversampling Techniques for Class Imbalance Problem Based on SMOTE
Description:

This package provides a collection of various oversampling techniques developed from SMOTE is provided. SMOTE is a oversampling technique which synthesizes a new minority instance between a pair of one minority instance and one of its K nearest neighbor. Other techniques adopt this concept with other criteria in order to generate balanced dataset for class imbalance problem.

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