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AEP (version 0.1.4)

paep: Computing the cumulative distribution function (cdf) of asymmetric exponential power (AEP) distribution.

Description

Computes the cdf of AEP distribution given by $$ F_{X}(x|\Theta)= \frac{1-\epsilon}{2}-\frac{1-\epsilon}{2 \Gamma\bigl(1+\frac{1}{\alpha}\bigr)} \gamma\Bigl(\Big|\frac{\mu-x}{\sigma(1-\epsilon)}\Big|^{\alpha},\frac{1}{\alpha}\Bigr),~{}~x < \mu, $$ $$ F_{X}(x|\Theta)= \frac{1-\epsilon}{2}+\frac{1+\epsilon}{2 \Gamma\bigl(1+\frac{1}{\alpha}\bigr)} \gamma\Bigl(\Big|\frac{x-\mu}{\sigma(1+\epsilon)}\Big|^{\alpha},\frac{1}{\alpha}\Bigr),~{{}}~x \geq \mu, $$ where \(-\infty<x<+\infty\), \(\Theta=(\alpha,\sigma,\mu,\epsilon)^T\) with \(0<\alpha \leq 2\), \(\sigma> 0\), \(-\infty<\mu<\infty\), and \(-1<\epsilon<1\).

Usage

paep(x, alpha, sigma, mu, epsilon, log.p = FALSE, lower.tail = TRUE)

Value

Computed cdf of AEP distribution at points of vector \(x\).

Arguments

x

Vector of observations.

alpha

Tail thickness parameter.

sigma

Scale parameter.

mu

Location parameter.

epsilon

Skewness parameter.

log.p

If TRUE, then log\( \bigl(F_{X}(x|\Theta)\bigr)\) is returned.

lower.tail

If FALSE, then \(1-F_{X}(x|\Theta)\) is returned.

Author

Mahdi Teimouri

Examples

Run this code
paep(x = 2, alpha = 1.5, sigma = 1, mu = 0, epsilon = 0.5, log.p = FALSE, lower.tail = TRUE)

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