Probability of correct selection (PCS) for selecting t out of k populations

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Description

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.

Usage

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

Arguments

theta

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

T

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

m

Number of nodes employed in the Gauss-Hermite quadrature

tol

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

Details

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).

Value

The probability of correct selection.

Author(s)

Jason Wilson, <jason.wilson@biola.edu>

References

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