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The IUP Journal of Computer Sciences

A New Generalization of Quasi Lindley Distribution with Lifetime Data

Article Details

Pub. Date	: Oct, 2021
Product Name	: The IUP Journal of Computer Sciences
Product Type	: Article
Product Code	: IJCS41021
Author Name	: Showkat A Dar, Aafaq A Rather and S Palanivel
Availability	: YES
Subject/Domain	: Management
Download Format	: PDF Format
No. of Pages	: 15

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Abstract

The paper introduces a new model of Quasi Lindley Distribution (QLD) using the length biased technique known as Length Biased Quasi Lindley (LBQL) distribution, and obtains different statistical and mathematical properties of the newly introduced distribution. It also obtains parameters by applying the maximum likelihood estimation technique and also discusses Fisher information matrix. Finally, a newly proposed model is demonstrated with an application to illustrate the superiority of model in modeling the real lifetime data.

Introduction

The newly introduced two-parametric probability model, known as Quasi Lindley Distribution (QLD), was introduced by Shanker and Mishra (2013), of which the lindley distribution is a particular case of it. Shanker has also obtained its various structural properties, including its moments, failure rate function, mean residual life function and stochastic ordering. Also, it is observed that the expressions for failure rate function, mean residual life function and stochastic ordering of the proposed quasi lindley distribution have better flexibility over lindley and exponential distribution. Quasi lindley distribution is a two-parametric probability distribution, but its various expressions like coefficient of skewness, variation and kurtosis depend upon only one parameter. Method of moments and maximum likelihood estimate is also used for parameter estimation. The proposed QLD also provides better fit in handling lifetime data over lindley distribution.