PofCSt: Probability of correct selection (PCS) for selecting t out of...

Description Usage Arguments Details Value Author(s) References See Also

View source: R/zs.PCS.master02.R


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, <[email protected]>


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. http://www.bubbs.biola.edu/~jason.wilson/Article2_tech_techreport.pdf
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 May 30, 2017, 12:39 a.m.