Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application

Finite mixture models provide a flexible tool for handling heterogeneous data. This paper introduces a new mixture model which is the mixture of Lindley and lognormal distributions (MLLND). First, the model is formulated, and some of its statistical properties are st...

Full description

Saved in:
Bibliographic Details
Main Author: A. S. Al-Moisheer
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Journal of Function Spaces
Online Access:http://dx.doi.org/10.1155/2021/9358496
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832552546546221056
author A. S. Al-Moisheer
author_facet A. S. Al-Moisheer
author_sort A. S. Al-Moisheer
collection DOAJ
description Finite mixture models provide a flexible tool for handling heterogeneous data. This paper introduces a new mixture model which is the mixture of Lindley and lognormal distributions (MLLND). First, the model is formulated, and some of its statistical properties are studied. Next, maximum likelihood estimation of the parameters of the model is considered, and the performance of the estimators of the parameters of the proposed models is evaluated via simulation. Also, the flexibility of the proposed mixture distribution is demonstrated by showing its superiority to fit a well-known real data set of 128 bladder cancer patients compared to several mixture and nonmixture distributions. The Kolmogorov Smirnov test and some information criteria are used to compare the fitted models to the real dataset. Finally, the results are verified using several graphical methods.
format Article
id doaj-art-114804637c774dc885317a23e48c0ac5
institution Kabale University
issn 2314-8888
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Journal of Function Spaces
spelling doaj-art-114804637c774dc885317a23e48c0ac52025-02-03T05:58:22ZengWileyJournal of Function Spaces2314-88882021-01-01202110.1155/2021/9358496Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and ApplicationA. S. Al-Moisheer0Department of MathematicsFinite mixture models provide a flexible tool for handling heterogeneous data. This paper introduces a new mixture model which is the mixture of Lindley and lognormal distributions (MLLND). First, the model is formulated, and some of its statistical properties are studied. Next, maximum likelihood estimation of the parameters of the model is considered, and the performance of the estimators of the parameters of the proposed models is evaluated via simulation. Also, the flexibility of the proposed mixture distribution is demonstrated by showing its superiority to fit a well-known real data set of 128 bladder cancer patients compared to several mixture and nonmixture distributions. The Kolmogorov Smirnov test and some information criteria are used to compare the fitted models to the real dataset. Finally, the results are verified using several graphical methods.http://dx.doi.org/10.1155/2021/9358496
spellingShingle A. S. Al-Moisheer
Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application
Journal of Function Spaces
title Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application
title_full Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application
title_fullStr Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application
title_full_unstemmed Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application
title_short Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application
title_sort mixture of lindley and lognormal distributions properties estimation and application
url http://dx.doi.org/10.1155/2021/9358496
work_keys_str_mv AT asalmoisheer mixtureoflindleyandlognormaldistributionspropertiesestimationandapplication