Extension of Comparative Analysis of Estimation Methods for Dirichlet Distribution Parameters

1
Halid, M.A
Halid, M.A
2
Halid
Halid
3
M.A .
M.A .
4
Akomolafe
Akomolafe
5
A.A.
A.A.
6
Oyegoke
Oyegoke
7
O.A.  Oladimeji O.A.
O.A. Oladimeji O.A.
1 Federal University of Technology

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The Dirichlet distribution is a generalization of the Beta distribution. This research deals with the estimation of scale parameter for Dirichlet distribution with known shapes. We examined three methods to estimate the parameters of Dirichlet distribution which are Maximum Likelihood Estimator, Method of Moment Estimator and Quasi-Likelihood Estimator. The performance of these methods were compared at different sample sizes using Bias, Mean Square Error, Mean Absolute Error and Variance criteria, an extensive simulation study was carried out on the basis of the selected criterion using statistical software packages as well as the application of the criterion to real life data, all these were done to obtain the most efficient method. The simulation study and analysis revealed that Quasi-Likelihood Estimator perform better in terms of bias while Method of Moment Estimator is better than the other two methods in terms of variance; the Maximum Likelihood Estimation was the best estimation method in terms of the Mean square Error and Mean Absolute Error; while Quasi-Likelihood Estimation method was the best estimation method with real life data.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

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Not applicable for this article.

Halid, M.A. 2020. \u201cExtension of Comparative Analysis of Estimation Methods for Dirichlet Distribution Parameters\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 20 (GJSFR Volume 20 Issue F6): .

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GJSFR Volume 20 Issue F6
Pg. 41- 55
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Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-F Classification: MSC 2010: 97K80
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v1.2

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September 30, 2020

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English

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The Dirichlet distribution is a generalization of the Beta distribution. This research deals with the estimation of scale parameter for Dirichlet distribution with known shapes. We examined three methods to estimate the parameters of Dirichlet distribution which are Maximum Likelihood Estimator, Method of Moment Estimator and Quasi-Likelihood Estimator. The performance of these methods were compared at different sample sizes using Bias, Mean Square Error, Mean Absolute Error and Variance criteria, an extensive simulation study was carried out on the basis of the selected criterion using statistical software packages as well as the application of the criterion to real life data, all these were done to obtain the most efficient method. The simulation study and analysis revealed that Quasi-Likelihood Estimator perform better in terms of bias while Method of Moment Estimator is better than the other two methods in terms of variance; the Maximum Likelihood Estimation was the best estimation method in terms of the Mean square Error and Mean Absolute Error; while Quasi-Likelihood Estimation method was the best estimation method with real life data.

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Extension of Comparative Analysis of Estimation Methods for Dirichlet Distribution Parameters

Halid
Halid
M.A .
M.A .
Akomolafe
Akomolafe
A.A.
A.A.
Oyegoke
Oyegoke
O.A.  Oladimeji O.A.
O.A. Oladimeji O.A.

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