gevrPbScore: GEVr Parametric Bootstrap Score Test

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

Description

Parametric bootstrap score test procedure to assess goodness-of-fit to the GEVr distribution.

Usage

gevrPbScore(
  data,
  bootnum,
  information = c("expected", "observed"),
  allowParallel = FALSE,
  numCores = 1
)

Arguments

data	Data should be contain n rows, each a GEVr observation.
bootnum	Number of bootstrap replicates.
information	To use expected (default) or observed information in the test.
allowParallel	Should the bootstrap procedure be run in parallel or not. Defaults to false.
numCores	If allowParallel is true, specify the number of cores to use.

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.

Value

statistic	Test statistic.
p.value	P-value for the test.
theta	Initial value of theta used in the test.
effective_bootnum	Effective number of bootstrap replicates (only those that converged are used).

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

# Generate some data from GEVr

x <- rgevr(200, 5, loc = 0.5, scale = 1, shape = 0.25)
gevrPbScore(x, bootnum = 99)

eva documentation built on Jan. 13, 2021, 8:34 p.m.