raw_est_eep

This function serves as the optimization function for EEP at different locations of density change points.

Contains the framework of the estimation, sampling, and hypotheses testing for two special distributions (Exponentiated Exponential-Pareto and Exponentiated Inverse Gamma-Pareto) within the family of Generalized Exponentiated Composite distributions. The detailed explanation and the applications of these two distributions were introduced in Bowen Liu, Malwane M.A. Ananda (2022) <doi:10.1080/03610926.2022.2050399>, Bowen Liu, Malwane M.A. Ananda (2022) <doi:10.3390/math10111895>, and Bowen Liu, Malwane M.A. Ananda (2022) <doi:10.3390/app13010645>.

Bowen Liu

Generalized Exponentiated Composite Distributions

Malwane M.A. Ananda

Dwaipayan Mukhopadhyay

raw_est_eep function

<dl><dt>data</dt>
<dd>Observations.</dd>
<dt>init</dt>
<dd>The vector of initial values of the model parameters. The default is c(1,1).</dd>
<dt>lower_bound</dt>
<dd>The vector of the lower bound for the parameters. The default is c(0.01,0.01).</dd></dl>

Arguments

The Optimization Function for EEP Maximum Likelihood Estimation. — raw_est_eep

<dl>

<dt>data</dt>
<dd>Observations.</dd>


<dt>init</dt>
<dd>The vector of initial values of the model parameters. The default is c(1,1).</dd>


<dt>lower_bound</dt>
<dd>The vector of the lower bound for the parameters. The default is c(0.01,0.01).</dd>

</dl>

raw_est_eep: The Optimization Function for EEP Maximum Likelihood Estimation.

Description

Usage

Value

Arguments

Details

Examples