Computing Maximally Selected Gauss Statistics

Description

Computes the probability that a maximally selected gauss statistic is greater or equal to b.

Usage

pexactgauss(b, N, m, maxpts)
qexactgauss(p, N, m)

Details

Correlations from Schlittgen, normal probabilities by Genz/Bretz (see pmvnorm for details).

Value

The probability that, under the hypothesis of independence, a maximally selected gauss statistic greater equal b is observed. This ist exact whereas pSchlitt does not work as advertised.

Author(s)

Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>

References

Genz, A. (1992). Numerical computation of multivariate normal probabilities. Journal of Computational and Graphical Statistics, 1, 141–150

Genz, A. (1993). Comparison of methods for the computation of multivariate normal probabilities. Computing Science and Statistics, 25, 400–405

Schlittgen, R. (1999), Regression Trees for Survival Data - an Approach to Select Discontinuous Split Points by Rank Statistics. Biometrical Journal, 41(8), 943–954.

Examples

pexact <- pexactgauss(2.5, 20, 2:18)