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