pdf_eep

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

pdf_eep function

<dl><dt>theta</dt>
<dd>The location parameter for the base distribution (eta = 1). The value needs to be positive.</dd>
<dt>eta</dt>
<dd>The exponent parameter. The value provided needs to be positive.</dd>
<dt>data</dt>
<dd>Observations.</dd></dl>

Arguments

The probability function of EEP. — pdf_eep

<dl>

<dt>theta</dt>
<dd>The location parameter for the base distribution (eta = 1). The value needs to be positive.</dd>


<dt>eta</dt>
<dd>The exponent parameter. The value provided needs to be positive.</dd>


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

</dl>

pdf_eep: The probability function of EEP.

Description

Usage

Value

Arguments

Examples