eva (version 0.2.6)

gevrPbScore: GEVr Parametric Bootstrap Score Test

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.

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).

Details

GEVr data (in matrix x) should be of the form \(x[i,1] > x[i, 2] > \cdots > x[i, r]\) for each observation \(i = 1, \ldots, n\).

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

# NOT RUN {
# Generate some data from GEVr
# }
# NOT RUN {
x <- rgevr(200, 5, loc = 0.5, scale = 1, shape = 0.25)
gevrPbScore(x, bootnum = 99)
# }