law0034.GeneralizedExpPower: The Generalized Exponential Power Distribution

In PoweR: Computation of Power and Level Tables for Hypothesis Tests

Description

Random generation for the Generalized Exponential Power distribution with parameters t1, t2 and t3.

This generator is called by function gensample to create random variables based on its parameters.

Details

If t1, t2 and t3 are not specified they assume the default value of 0.5, 0 and 1, respectively.

The Generalized Exponential Power distribution has density:

p(x;γ,δ,α,β,z_0) \propto e^-(δ |x|^γ) |x|^(-α) log|x|^(-β)

for x ≥ z_0, and the density equals to p(x;γ,δ,α,β,z_0) for x < z_0.

Author(s)

P. Lafaye de Micheaux, V. A. Tran

References

Pierre Lafaye de Micheaux, Viet Anh Tran (2016). PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R. Journal of Statistical Software, 69(3), 1–42. doi:10.18637/jss.v069.i03

Desgagne, A., Lafaye de Micheaux, P. and Leblanc, A. (2013), Test of Normality Against Generalized Exponential Power Alternatives, Communications in Statistics - Theory and Methods, 42(1), 164–190.

See Also

See Distributions for other standard distributions.

Examples

res <- gensample(34,10000,law.pars=c(1,8,4))
res$law
res$law.pars
mean(res$sample)
sd(res$sample)

PoweR documentation built on May 2, 2019, 2:09 p.m.