PofCSt: Probability of Correct Selection (PCS) for Selecting t out of...

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PofCStR Documentation

Probability of Correct Selection (PCS) for Selecting t out of k Populations


Implementation of the Gupta & Liang (1998) formula for computing the probability of correct selection (PCS) for selecting t out of k populations. The results are exact up to a user-settable tolerance parameter. This function is modular and is called by PdofCSt.T1or2, PdofCSt.cyc2, and PofCSGt.


 PofCSt(theta, T, m, tol = 1e-07) 



Vector of statistics (or parameters) from which it is desired to select the top t of them


The number of statistics (or parameters) desired to be selected


Number of nodes employed in the Gauss-Hermite quadrature


Tolerance parameter to set the cut-off level for the inclusion of additional probability components in PCS


The analytic formula for computing PCS for t of k populations is an integral whose integrad is the product of normal densities. This function obtains the appropriate values and computes the integral using a Gauss-Hermite quadrature. See equation 2.4 of Gupta (1998).


The probability of correct selection.


Jason Wilson <jason.wilson@biola.edu>


Cui, X. and Wilson, J. 2007. On How to Calculate the Probability of Correct Selection for Large k Populations. University of California, Riverside Statistics Department Technical Report 297. https://docs.google.com/a/biola.edu/viewer?a=v&pid=sites&srcid=YmlvbGEuZWR1fGphc29ud2lsc29ufGd4OjJmYTY2YTJjY2EwYjg2ZmY
Gupta, S.S. and Liang, T.C. 1998. Simultaneous lower confidence bounds for probabilities of correct selections. Journal of Statistical Planning and Inference. 72(1-2), 279-290.

See Also

PdofCSt.T1or2, PdofCSt.cyc2, PofCSGt

PCS documentation built on June 21, 2022, 1:05 a.m.