Estimation of shape β parameter in Kumaraswamy distribution using Maximum Likelihood and Bayes method

H. G. Simbolon, Ida Fithriani, Siti Nurrohmah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper discusses the Maximum Likelihood (ML) and Bayes method for estimating the shape β parameter in Kumaraswamy distribution. Both methods will be compared according to Mean Square Error (MSE) obtained from each estimator. In the Bayes method, two Loss functions will be used, i.e., the Square Error Loss Function (SELF) and Precautionary Loss Function (PLF). Then, the Posterior Risk obtained from both loss functions will be compared. The comparison will be applied to hydrological data as a recommendation for the best method of representing the data. Hydrological data used in this study is a water storage in Shasta Reservoir, obtained from the California Data Exchange Center. By using the Mathematica Software and the formulas from both methods one obtains a statistic which can nicely describe the data and also predict the next observation of a reservoir in a certain time.

Original languageEnglish
Title of host publicationInternational Symposium on Current Progress in Mathematics and Sciences 2016, ISCPMS 2016
Subtitle of host publicationProceedings of the 2nd International Symposium on Current Progress in Mathematics and Sciences 2016
EditorsKiki Ariyanti Sugeng, Djoko Triyono, Terry Mart
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735415362
DOIs
Publication statusPublished - 10 Jul 2017
Event2nd International Symposium on Current Progress in Mathematics and Sciences 2016, ISCPMS 2016 - Depok, Jawa Barat, Indonesia
Duration: 1 Nov 20162 Nov 2016

Publication series

NameAIP Conference Proceedings
Volume1862
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2nd International Symposium on Current Progress in Mathematics and Sciences 2016, ISCPMS 2016
CountryIndonesia
CityDepok, Jawa Barat
Period1/11/162/11/16

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