law0034.GeneralizedExpPower {PoweR} | R Documentation |
The Generalized Exponential Power Distribution
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;\gamma,\delta,\alpha,\beta,z_0) \propto e^-{\delta|x|^\gamma} |x|^{-\alpha}(log|x|)^{-\beta}
for x \ge z_0
, and the density equals to p(x;\gamma,\delta,\alpha,\beta,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)