gevrEd: GEVr Entropy Difference Test

In eva: Extreme Value Analysis with Goodness-of-Fit Testing

GEVr Entropy Difference Test

Description

Goodness-of-fit test for GEVr using the difference in likelihood between GEVr and GEV(r-1). This can be used sequentially to test for the choice of r.

Usage

gevrEd(data, theta = NULL)

Arguments

data	Data should be contain n rows, each a GEVr observation.
theta	Estimate for theta in the vector form (loc, scale, shape). If NULL, uses the MLE from the full data.

Details

GEVr data (in matrix x) should be of the form x[i,1] > x[i, 2] > \cdots > x[i, r] for each observation i = 1, \ldots, n. The test uses an asymptotic normality result based on the expected entropy between the GEVr and GEV(r-1) likelihoods. See reference for detailed information. This test can be used to sequentially test for the choice of r, implemented in the function ‘gevrSeqTests’.

Value

statistic	Test statistic.
p.value	P-value for the test.
theta	Estimate of theta using the top r order statistics.

References

Bader B., Yan J., & Zhang X. (2015). Automated Selection of r for the r Largest Order Statistics Approach with Adjustment for Sequential Testing. Department of Statistics, University of Connecticut.

Examples

## This will test if the GEV2 distribution fits the data.
x <- rgevr(100, 2, loc = 0.5, scale = 1, shape = 0.5)
result <- gevrEd(x)

eva documentation built on June 21, 2026, 9:07 a.m.