GEVr Entropy Difference Test

Share:

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

1
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, …, 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

1
2
3
## 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)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.