The topp-leone generalized exponential power series distribution

Name: Natcha Kunjiratanachot

LCSH: Kasetsart University -- Dissertations. Ph.D. (Statistics) 2019

Classification :.LCCS: QA273.6

LCSH: Kasetsart University. -- Department of Statistics -- Dissertations

LCSH: Distribution (Probability theory)

LCSH: Exponential families (Statistics)

LCSH: Binomial theorem

LCSH: Binomial distribution

LCSH: Parameter estimation

Abstract: A new family of distributions is presented in this thesis namely the ToppLeone generalized exponential power series distribution. It is gained by compounding a lifetime distribution with discrete distributions. They are utilized in reliability analysis of parallel process with independent and identically distributed components. The lifetime of each component is distributed as the Topp-Leone generalized exponential distribution. The proposed distribution can be employed by several lifetime models. There are some special cases of the Topp-Leone generalized exponential power series distribution such as the Topp-Leone generalized exponential geometric, ToppLeone generalized exponential Poisson, Topp-Leone generalized exponential binomial, and Topp-Leone generalized exponential logarithmic distributions. Some statistical properties of the proposed distributions are presented including the cumulative distribution function, survival function, hazard function and moments. In this thesis, the Topp-Leone generalized exponential geometric distribution will be illustrated some properties. The parameter estimation methods used for the Topp-Leone generalized exponential geometric are the maximum likelihood estimation, least square estimation and Anderson-Darling estimation. Simulation study is employed for the maximum likelihood estimation gives the root mean square error tends to decrease when sample sizes increase. Finally, some datasets are applied by fitting with the generalized exponential, Topp-Leone generalized exponential, Topp-Leone generalized exponential geometric and Topp-Leone generalized exponential Poisson distributions. The results show that its sub-model of the proposed distribution is better than selected distributions. Therefore, the proposed distribution is an alternative distribution for lifetime data.

Kasetsart University. Office of the University Library

Address: Bangkok

Email: tdckulib@ku.ac.th

Name: Winai Bodhisuwan

Role: Thesis Advisor

Created: 2019

Modified: 2025-06-27

Issued: 2025-06-27

วิทยานิพนธ์/Thesis

application/pdf

URL: https://www.lib.ku.ac.th/KUthesis/2562/natcha-kun-all.pdf

CallNumber: QA273.6 .N39

eng

DegreeName: Doctor of Philosophy

Level: Doctoral Degraee

Descipline: Statistics

Grantor: Kasetsart University

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