Create Dashboards with 'Shiny'

Create dashboards with 'Shiny'. This package provides a theme on top of 'Shiny', making it easy to create attractive dashboards.

Object Pooling

Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are 'DBI' connections.

'WebSocket' Client Library

Provides a 'WebSocket' client interface for R. 'WebSocket' is a protocol for low-overhead real-time communication: < https://en.wikipedia.org/wiki/WebSocket>.

Pulls Information from Prov.Json Files

R functions to access provenance information collected by 'rdt' or 'rdtLite'. The information is stored inside a 'ProvInfo' object and can be accessed through a collection of functions that will return the requested data. The exact format of the JSON created by 'rdt' and 'rdtLite' is described in < https://github.com/End-to-end-provenance/ExtendedProvJson>.

Web Application Framework for R

Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.

Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests

Provides (1) pseudo random generators - general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm () and WELL () generators); (2) quasi random generators - the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some generator tests - the gap test, the serial test, the poker test, see, e.g., Gentle (2003) . Take a look at the Distribution task view of types and tests of random number generators. The package can be provided without the 'rngWELL' dependency on demand. Package in Memoriam of Diethelm and Barbara Wuertz.

R Markdown Format for Flexible Dashboards

Format for converting an R Markdown document to a grid oriented dashboard. The dashboard flexibly adapts the size of it's components to the containing web page.

Stability-enHanced Approaches using Resampling Procedures

In stability selection (N Meinshausen, P Bühlmann (2010) ) and consensus clustering (S Monti et al (2003) ), resampling techniques are used to enhance the reliability of the results. In this package (B Bodinier et al (2025) ), hyper-parameters are calibrated by maximising model stability, which is measured under the null hypothesis that all selection (or co-membership) probabilities are identical (B Bodinier et al (2023a) and B Bodinier et al (2023b) ). Functions are readily implemented for the use of LASSO regression, sparse PCA, sparse (group) PLS or graphical LASSO in stability selection, and hierarchical clustering, partitioning around medoids, K means or Gaussian mixture models in consensus clustering.

Flexible Data Simulation Using the Multivariate Normal Distribution

This R package can be used to generate artificial data conditionally on pre-specified (simulated or user-defined) relationships between the variables and/or observations. Each observation is drawn from a multivariate Normal distribution where the mean vector and covariance matrix reflect the desired relationships. Outputs can be used to evaluate the performances of variable selection, graphical modelling, or clustering approaches by comparing the true and estimated structures (B Bodinier et al (2021) ).

Acesso aos Dados do 'SIDRA' do IBGE

Functions for accessing and manipulating data from Brazilian Institute of Geography and Statistics (IBGE)'s API 'SIDRA' (acronym for IBGE System of Automatic Retrieval) from the new endpoints at < https://servicodados.ibge.gov.br/api/docs/agregados?versao=3>. Ferramentas para acessar e manipular dados via API do Sistema IBGE De Recuperação Automática 'SIDRA' do Instituto Brasileiro de Geografia e Estatística (IBGE).