R: Computing Maximally Selected Gauss Statistics

pexactgauss {maxstat} | R Documentation

## Computing Maximally Selected Gauss Statistics

### Description

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

### Usage

    pexactgauss(b, x, minprop=0.1, maxprop=0.9, ...)
    qexactgauss(p, x, minprop=0.1, maxprop=0.9, ...)

### Arguments

`b` | quantile.
`p` | probability.
`x` | the prognostic factor(s) under test.
`minprop` | at least `minprop`*100% of the observations in the first group.
`maxprop` | not more than `minprop`*100% of the observations in the first group.
`...` | additional parameters to be passed to `pmvnorm`.

### Details

This is the exact distribution of a maximally selected Gauss statistic and the asymptotic distribution for maximally selected rank statistics. Normal probabilities are derived from the procedures 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.

### 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

### Examples

    set.seed(29)

    x <- rnorm(20)

    pexact <- pexactgauss(2.5, x, abseps=0.01)

[Package maxstat version 0.7-25 Index]