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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.
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.
Summarizes Provenance Related to Inputs and Outputs of a Script or Console Commands
Reads the provenance collected by the 'rdt' or
'rdtLite' packages, or other tools providing compatible PROV JSON output
created by the execution of a script, and provides a human-readable
summary identifying the input and output files, the script used
(if any), errors and warnings produced, and the environment in
which it was executed. It can also optionally package all the
files into a zip file. The exact format of the JSON created by
'rdt' and 'rdtLite' is described in
< https://github.com/End-to-end-provenance/ExtendedProvJson>.
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,
Epimed Solutions Collection for Data Editing, Analysis, and Benchmark of Health Units
Collection of functions for data analysis and editing of clinical and epidemiological data. Most of them are related to benchmark with prediction models.
Datasets for Agresti and Finlay's "Statistical Methods for the Social Sciences"
Datasets used in "Statistical Methods for the Social Sciences" (SMSS) by Alan Agresti and Barbara Finlay.
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>.
Discovery of Motifs in Spatial-Time Series
Allow to identify motifs in spatial-time series. A motif is a previously unknown subsequence of a (spatial) time series with relevant number of occurrences. For this purpose, the Combined Series Approach (CSA) is used.
Provenance Visualizer
Displays provenance graphically for provenance collected by the 'rdt' or
'rdtLite' packages, or other tools providing compatible PROV JSON output. The exact
format of the JSON created by 'rdt' and 'rdtLite' is described in
< https://github.com/End-to-end-provenance/ExtendedProvJson>. 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,
Turtle Graphics
An implementation of turtle graphics < http://en.wikipedia.org/wiki/Turtle_graphics>. Turtle graphics comes from Papert's language Logo and has been used to teach concepts of computer programming.
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.