GPS | R Documentation |
Applies the Gamma Poisson Shrinker (GPS) introduced by DuMouchel (1999) to a collection of 2 x 2 tables of the form
event | not event | |
drug | a | c |
not drug | b | d
|
GPS(
a,
b,
c,
d,
E = ((a + b) * (a + c))/(a + b + c + d),
prior = fitPriorParametersGPS(a, b, c, d),
alpha = NULL
)
a |
A vector with the counts of the upper left corner of the tables |
b |
A vector with the counts of the lower left corner of the tables |
c |
A vector with the counts of the upper right corner of the tables |
d |
A vector with the counts of the lower right corner of the tables |
E |
Vector with the expected values when there are no associations. By default set to
the values used by DuMouchel (1999), i.e., |
prior |
List that contains the prior parameters. If not specified, automatically fitted to the data,
see |
alpha |
Value between |
a vector with the GPS estimates
DuMouchel, W. (1999). Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System. The American Statistician, 53(3), 177–190. https://doi.org/10.1080/00031305.1999.10474456
DuMouchel, W., & Pregibon, D. (2001). Empirical bayes screening for multi-item associations. Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’01, (October), 67–76. http://doi.org/10.1145/502512.502526
fitPriorParametersGPS()
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