Warsono, Warsono and Husaini, Oktarini and Aziz, Dorrah and Usman, Mustofa and Wamiliana, Wamiliana (2018) CHARACTERISTICS OF KUMARASWAMY DISTRIBUTION PARAMETERESTIMATIONWITH PROBABILITY WEIGHTED MOMENT (PWM) AND MAXIMUM LIKELIHOOD ESTIMATION (MLE) METHODS. Science International Lahore, 30 (5). pp. 697-701. ISSN 1013-5316
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Abstract
ABSTRACT: The distribution of Kumaraswamy has two parameters namely (a, b) with parameters a and b are shape parameters which show the shape of the curve. This Kumaraswamy distribution parameter estimation is obtained by using Probability Weighted Moment (PWM) and Maximum Likelihood Estimation (MLE) methods. This study examined the characteristics of Kumaraswamy distribution parameters estimator (a, b) using the Probability Weighted Moment (PWM) method and Maximum Likelihood Estimation (MLE) method which includes unbiased, minimum variance, consistency, and sufficient statistics characteristics. The results indicated that parameter estimators (a, b) have good estimator characteristics which are unbiased, consistent, minimum variance, and sufficient statistics to attain the Cramer-Rao lower bound. Keywords: Kumaraswamy Distribution, Probability Weighted Moment (PWM), Maximum Likelihood Estimation (MLE), Unbiased, minimum variance.
| Item Type: | Article |
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| Subjects: | Q Science > QA Mathematics |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika |
| Depositing User: | WAMILIANA |
| Date Deposited: | 24 Oct 2018 01:49 |
| Last Modified: | 24 Oct 2018 01:49 |
| URI: | http://repository.lppm.unila.ac.id/id/eprint/8814 |
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