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

PofCSt | R Documentation |

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)

`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 |

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.

`PdofCSt.T1or2`

, `PdofCSt.cyc2`

, `PofCSGt`

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