gpdImAsym {eva}

GPD Asymptotic Adjusted Information Matrix (IM) Test

Description

Runs the IM Test using bootstrap estimated covariance matrix. Asymptotically (in sample size) follows the F(3, bootnum - 3) distribution (see reference for details).

Usage

gpdImAsym(data, bootnum, theta = NULL)

Arguments

data

Data should be in vector form.

bootnum

Number of bootstrap replicates for the covariance estimate.

theta

Estimate for theta in the vector form (scale, shape). If NULL, uses the MLE.

Value

statistic

Test statistic.

p.value

P-value for the test.

theta

Value of theta used in the test.

effective_bootnum

Effective number of bootstrap replicates used for the covariance estimate. If a replicate fails to converge, it will not be used in the estimation.

References

Dhaene, G., & Hoorelbeke, D. (2004). The information matrix test with bootstrap-based covariance matrix estimation. Economics Letters, 82(3), 341-347.

Examples

# Generate some data from GPD
x <- rgpd(200, loc = 0, scale = 1, shape = 0.2)
gpdImAsym(x, bootnum = 50)