EM Algorithm for Estimating the Parameters of Quasi-Lindley Model with Application

EM Algorithm for Estimating the Parameters of Quasi-Lindley Model with Application

The quasi-Lindley distribution is a flexible model useful in reliability analysis, management science, and engineering analysis. In this paper, an expectation-maximization (EM) algorithm was applied to estimate the parameters of this model for uncensored and right-censored data. Simulation studies s...

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Bibliographic Details
Published in:Journal of mathematics (Hidawi) Vol. 2022; no. 1
Main Authors: Kayid, M., Al-Maflehi, Nassr S.
Format: Journal Article
Language:English
Published: Cairo Hindawi 2022
Hindawi Limited
Subjects:
Algorithms
Censorship
Mathematical models
Mathematics
Maximum likelihood estimates
Parameters
Random variables
Reliability analysis
Reliability engineering
Simulation
Survival analysis
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Description
Summary:The quasi-Lindley distribution is a flexible model useful in reliability analysis, management science, and engineering analysis. In this paper, an expectation-maximization (EM) algorithm was applied to estimate the parameters of this model for uncensored and right-censored data. Simulation studies show that the estimates of EM perform better than maximum likelihood estimates (MLEs) for both uncensored and censored data. In an illustrative example, the waiting times of a bank’s customers are analyzed and the estimator of the EM algorithm is compared with the MLE. The analysis of the data can be useful for the management of the bank.
ISSN:2314-4629
2314-4785
DOI:10.1155/2022/8467291