rasubbo: Produces a random sample from a Asymmetric Power Exponential...

In Rsubbotools: Fast Estimation of Subbottin and AEP Distributions (Generalized Error Distribution)

Produces a random sample from a Asymmetric Power Exponential distribution

Description

Generate pseudo random-number from an asymmetric power exponential distribution using the Tadikamalla method. This version improves on Bottazzi (2004) by making the mass of each distribution to depend on the ratio between the al and the ar parameters.

Usage

rasubbo(n, m = 0, al = 1, ar = 1, bl = 2, br = 2)

Arguments

n	(int) - size of the sample.
m	(numeric) - location parameter.
al, ar	(numeric) - scale parameters.
bl, br	(numeric) - shape parameters.

Details

The AEP distribution is expressed by the function:

f(x;a_l,a_r,b_l,b_r,m) = \frac{1}{A} e^{- \frac{1}{b_l} |\frac{x-m}{a_l}|^{b_l} }, x < m

f(x;a_l,a_r,b_l,b_r,m) = \frac{1}{A} e^{- \frac{1}{b_r} |\frac{x-m}{a_r}|^{b_r} }, x > m

with:

A = a_lb_l^{1/b_l}\Gamma(1+1/b_l) + a_rb_r^{1/b_r}\Gamma(1+1/b_r)

where m is a location parameter, b* are shape parameters, a* are scale parameters and \Gamma representes the gamma function. By a suitably transformation, it is possible to use the EP distribution with the Tadikamalla method to sample from this distribution. We basically take the absolute values of the numbers sampled from the rpower function, which is equivalent from sampling from a half Exponential Power distribution. These values are then weighted by a constant expressed in the parameters. More details are available on the package vignette and on the function rpower.

Value

a numeric vector containing a random sample.

Examples

sample_gamma <- rasubbo(1000, 0, 0.5, 0.5,  1, 1)

Rsubbotools documentation built on April 16, 2025, 5:10 p.m.