openEBGM: EBGM Scores for Mining Large Contingency Tables

An implementation of DuMouchel's (1999) <doi:10.1080/00031305.1999.10474456> Bayesian data mining method for the market basket problem. Calculates Empirical Bayes Geometric Mean (EBGM) and quantile scores from the posterior distribution using the Gamma-Poisson Shrinker (GPS) model to find unusually large cell counts in large, sparse contingency tables. Can be used to find unusually high reporting rates of adverse events associated with products. In general, can be used to mine any database where the co-occurrence of two variables or items is of interest. Also calculates relative and proportional reporting ratios. Builds on the work of the 'PhViD' package, from which much of the code is derived. Some of the added features include stratification to adjust for confounding variables and data squashing to improve computational efficiency.

Version: 0.1.0
Depends: R (≥ 3.2.3)
Imports: data.table (≥ 1.10.0), ggplot2 (≥ 2.2.1), stats (≥ 3.2.3)
Suggests: dplyr (≥ 0.5.0), knitr (≥ 1.15.1), rmarkdown (≥ 1.2), testthat (≥ 1.0.2), tidyr (≥ 0.6.0)
Published: 2017-05-05
Author: John Ihrie [cre, aut], Travis Canida [aut], Ismaïl Ahmed [ctb] (author of 'PhViD' package (derived code)), Antoine Poncet [ctb] (author of 'PhViD' package (derived code))
Maintainer: John Ihrie <John.Ihrie at>
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: openEBGM results


Reference manual: openEBGM.pdf
Vignettes: Introduction to openEBGM
Processing Raw Data with openEBGM
Hyperparamter Estimation with openEBGM
Empirical Bayes Metrics with openEBGM
openEBGM Objects, Class Functions and Individual Calculations
Package source: openEBGM_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: openEBGM_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: openEBGM_0.1.0.tgz


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