Topp-leone inverse gompertz distribution: properties and different estimations techniques and applications | [Pakistan Journal of Statistics • 2023]

Author(s):

1. Taiwo Mobolaji Adegoke: Deptt. of Mathematics and Statistics, First Technical University Ibadan, Nigeria.

2. Oladapo Muyiwa Oladoja: Deptt. of Mathematics and Statistics, First Technical University Ibadan, Nigeria.

3. Sule Omeiza Bashiru: Deptt. of Mathematical Sciences, Prince Abubakar Audu University Anyigba, Kogi State, Nigeria.

4. Aliyu Abba Mustapha: Deptt. of Mathematical Sciences, University of Maiduguri Borno State, Nigeria.

5. Dimeji Ebenezer Aderupatan: Deptt. of Mathematical Sciences, University of Maiduguri Borno State, Nigeria.

6. Lawrence Chukwudumebi Nzei: Deptt. of Statistics, University of Benin, Benin City, Nigeria.

Abstract:

In this work, we proposed a new probability distribution based on the extension of the Gompertz distribution for modeling life time datasets known as the “Topp-Leone Inverse Gompertz Distribution (TLIG distribution)”. The TLIG distribution is derived using the logit of Topp-Leone generator and the Inverse Gompertz distribution (IGD) as the baseline distribution. Properties of TLIG distribution were examined. Five different estimation techniques namely maximum likelihood estimate (MLE), Weighted Least Squares Estimates (WLS), Ordinary Least Squares Estimates (OLS), Crammer-Von Miss Estimate (CVME) and Percentile Estimate (PCE) were considered to estimate the parameters of TLIG distribution. A Monte Carlo simulation technique was adopted to assess the consistency and efficiency of these parameter estimates. The usefulness of this new distribution is demonstrated with two real-life datasets whose results shows that the new TLIG distribution performs better than some familiar existing distribution.

Page(s): 433-456

DOI: DOI not available

Published: Journal: Pakistan Journal of Statistics, Volume: 39, Issue: 4, Year: 2023

Keywords:

Monte Carlo simulation , ToppLeone distribution , Inverse Gompertz , Least Squares Estimates , CrammerVon Miss Estimate , Odd function

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