Provides the Jester Dataset for recommenderlab
Freely available for research use when acknowledged with the
following reference: Eigentaste: A Constant Time Collaborative
Filtering Algorithm. Ken Goldberg, Theresa Roeder, Dhruv Gupta,
and Chris Perkins. Information Retrieval, 4(2), 133-151. July
2001.

Provides the Jester Dataset for package recommenderlab.

Reconstruct Individual-Level Data from Published KM Plots
Functions for reconstructing individual-level data (time, status, arm) from Kaplan-MEIER curves published in academic journals (e.g. NEJM, JCO, JAMA). The individual-level data can be used for re-analysis, meta-analysis, methodology development, etc. This package was used to generate the data for commentary such as Sun, Rich, & Wei (2018) <doi:10.1056/NEJMc1808567>. Please see the vignette for a quickstart guide.
stats, dplyr, magrittr, survival, rlang, stats4, survminer

Functions to aid in reconstructing sessions
and efficiently calculating an array of metrics from the resulting data,
including bounce rate, time-on-page, and session length. Although primarily
designed for web data and analytics, its approach is plausibly applicable
to other domains.

Functions to reconstruct sessions from web log or other user trace data
and calculate various metrics around them, producing tabular,
output that is compatible with 'dplyr' or 'data.table' centered processes.

Toolkit to Validate New Data for a Predictive Model
A lightweight toolkit to validate new observations when computing
their predictions with a predictive model. The validation process
consists of two steps: (1) record relevant statistics and meta data of the
variables in the original training data for the predictive model and
(2) use these data to run a set of basic validation tests on the new set of
observations.

c( person("Peter", "Slaughter", role = c("aut", "cre"), email = "slaughter@nceas.ucsb.edu"),
person("Matthew", "Jones", role = "aut", email = "jones@nceas.ucsb.edu"),
person("Chris", "Jones", role = "ctb", email = "cjones@nceas.ucsb.edu"),
person("Lauren", "Palmer", role = "ctb", email = "walker@nceas.ucsb.edu")  )
Provide methods to record data provenance about R script
executions. Provenance data includes files that were read and written by
the script, along with information about the execution, such as start time
end time, the R modules loaded during the execution, and other information
describing the execution environment.
dataone, ggplot2, knitr, png, testthat, rmarkdown
'Constants.R' 'Recordr.R' 'ExecMetadata.R' 'FileMetadata.R'
'onLoad.R' 'recordr-package.R' 'tracedFunctions.R'
Peter Slaughter [aut, cre],
Matthew Jones [aut],
Chris Jones [ctb],
Lauren Palmer [ctb]