Create Dashboards with 'Shiny'

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

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.

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.

Half-Normal Plots with Simulation Envelopes

Generates (half-)normal plots with simulation envelopes using different diagnostics from a range of different fitted models. A few example datasets are included.

Provenance Collector

Defines functions that can be used to collect provenance as an 'R' script executes or during a console session. The output is a text file in 'PROV-JSON' format.

Epimed Solutions Collection for Data Editing, Analysis, and Benchmark of Health Units

Collection of functions related to benchmark with prediction models for data analysis and editing of clinical and epidemiological data.

Compare Provenance Collections to Explain Changed Script Outputs

Inspects provenance collected by the 'rdt' or 'rdtLite' packages, or other tools providing compatible PROV JSON output created by the execution of a script, and find differences between two provenance collections. Factors under examination included the hardware and software used to execute the script, versions of attached libraries, use of global variables, modified inputs and outputs, and changes in main and sourced scripts. Based on detected changes, 'provExplainR' can be used to study how these factors affect the behavior of the script and generate a promising diagnosis of the causes of different script results. More information about 'rdtLite' and associated tools is available at < https://github.com/End-to-end-provenance/> and Barbara Lerner, Emery Boose, and Luis Perez (2018), Using Introspection to Collect Provenance in R, Informatics, .

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.

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) ).