Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data

Aims: In this study a survival mixture model of three components is considered to analyse survival data of heterogeneous nature.The survival mixture model is of the Exponential, Gamma and Weibull distributions.Methodology: The proposed model was investigated and the Maximum Likelihood (ML) estimator...

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Main Authors: Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah
Format: Article
Language:English
Published: SCIENCEDOMAIN international 2015
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Online Access:http://repo.uum.edu.my/17624/1/JSRR_5_2_132_139.pdf
http://repo.uum.edu.my/17624/
http://doi.org/10.9734/JSRR/2015/15014
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spelling my.uum.repo.176242016-04-27T06:55:37Z http://repo.uum.edu.my/17624/ Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data Mohammed, Yusuf Abbakar Yatim, Bidin Ismail, Suzilah QA75 Electronic computers. Computer science Aims: In this study a survival mixture model of three components is considered to analyse survival data of heterogeneous nature.The survival mixture model is of the Exponential, Gamma and Weibull distributions.Methodology: The proposed model was investigated and the Maximum Likelihood (ML) estimators of the parameters of the model were evaluated by the application of the Expectation Maximization Algorithm (EM).Graphs, log likelihood (LL) and the Akaike Information Criterion (AIC) were used to compare the proposed model with the pure classical parametric survival models corresponding to each component using real survival data.The model was compared with the survival mixture models corresponding to each component.Results: The graphs, LL and AIC values showed that the proposed model fits the real data better than the pure classical survival models corresponding to each component.Also the proposed model fits the real data better than the survival mixture models corresponding to each component. Conclusion: The proposed model showed that survival mixture models are flexible and maintain the features of the pure classical survival model and are better option for modelling heterogeneous survival data. SCIENCEDOMAIN international 2015 Article PeerReviewed application/pdf en http://repo.uum.edu.my/17624/1/JSRR_5_2_132_139.pdf Mohammed, Yusuf Abbakar and Yatim, Bidin and Ismail, Suzilah (2015) Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data. Journal of Scientific Research and Reports, 5 (2). pp. 132-139. ISSN 2320-0227 http://doi.org/10.9734/JSRR/2015/15014 doi:10.9734/JSRR/2015/15014
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohammed, Yusuf Abbakar
Yatim, Bidin
Ismail, Suzilah
Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
description Aims: In this study a survival mixture model of three components is considered to analyse survival data of heterogeneous nature.The survival mixture model is of the Exponential, Gamma and Weibull distributions.Methodology: The proposed model was investigated and the Maximum Likelihood (ML) estimators of the parameters of the model were evaluated by the application of the Expectation Maximization Algorithm (EM).Graphs, log likelihood (LL) and the Akaike Information Criterion (AIC) were used to compare the proposed model with the pure classical parametric survival models corresponding to each component using real survival data.The model was compared with the survival mixture models corresponding to each component.Results: The graphs, LL and AIC values showed that the proposed model fits the real data better than the pure classical survival models corresponding to each component.Also the proposed model fits the real data better than the survival mixture models corresponding to each component. Conclusion: The proposed model showed that survival mixture models are flexible and maintain the features of the pure classical survival model and are better option for modelling heterogeneous survival data.
format Article
author Mohammed, Yusuf Abbakar
Yatim, Bidin
Ismail, Suzilah
author_facet Mohammed, Yusuf Abbakar
Yatim, Bidin
Ismail, Suzilah
author_sort Mohammed, Yusuf Abbakar
title Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
title_short Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
title_full Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
title_fullStr Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
title_full_unstemmed Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
title_sort mixture model of the exponential, gamma and weibull distributions to analyse heterogeneous survival data
publisher SCIENCEDOMAIN international
publishDate 2015
url http://repo.uum.edu.my/17624/1/JSRR_5_2_132_139.pdf
http://repo.uum.edu.my/17624/
http://doi.org/10.9734/JSRR/2015/15014
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score 13.160551