fitaep

Estimates the parameters of AEP distribution.

Developed for Computing the probability density function, cumulative
distribution function, random generation, estimating the parameters of asymmetric
exponential power distribution, and robust regression analysis with error
term that follows asymmetric exponential power distribution. The asymmetric
exponential power distribution studied here is a special case of that introduced
by Dongming and Zinde-Walsh (2009) <doi:10.1016/j.jeconom.2008.09.038>.

Mahdi Teimouri

Statistical Modelling for Asymmetric Exponential Power
Distribution

fitaep function

<dl><dt>x</dt>
<dd>Vector of observations.</dd><dt>initial</dt>
<dd>By default is <code>FALSE</code>. If the initial values are given by user, then set <code>initial=TRUE</code>.</dd><dt>starts</dt>
<dd>If initial values <code>starts</code>=\(\bigl(\alpha^{(0)}, \sigma^{(0)}, \mu^{(0)}, \epsilon^{(0)} \bigr)\), are given by user, i.e., <code>initial=TURE</code>, then vector <code>starts</code> must contain the initial values of the parameter vector, i.e., for starting the EM algorithm.</dd></dl>

Arguments

Author

Estimating the parameters of AEP distribution through the expectation-maximization (EM) algorithm — fitaep

<dl>

<dt>x</dt>
<dd>Vector of observations.</dd>

<dt>initial</dt>
<dd>By default is <code>FALSE</code>. If the initial values are given by user, then set <code>initial=TRUE</code>.</dd>

<dt>starts</dt>
<dd>If initial values <code>starts</code>=\(\bigl(\alpha^{(0)}, \sigma^{(0)}, \mu^{(0)}, \epsilon^{(0)} \bigr)\), are given by user, i.e., <code>initial=TURE</code>, then vector <code>starts</code> must contain the initial values of the parameter vector, i.e., for starting the EM algorithm.</dd>

</dl>

fitaep: Estimating the parameters of AEP distribution through the expectation-maximization (EM) algorithm

Description

Usage

Value

Arguments

Author

References

Examples