gpdPbScore: GPD 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 Generalized Pareto distribution.

Usage

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

Arguments

data	Data should be in vector form.
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	Estimated value of theta for the initial data.
effective_bootnum	Effective number of bootstrap replicates (only those that converged are used).

Examples

# Generate some data from GPD
x <- rgpd(200, loc = 0, scale = 1, shape = 0.2)
gpdPbScore(x, bootnum = 100)

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