Bayesian approach to generalized normal distribution under non-informative and informative priors
Автор: Saima Naqash, S.P.Ahmad, Aquil Ahmed
Журнал: International Journal of Mathematical Sciences and Computing @ijmsc
Статья в выпуске: 4 vol.4, 2018 года.
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The generalized Normal distribution is obtained from normal distribution by adding a shape parameter to it. This paper is based on the estimation of the shape and scale parameter of generalized Normal distribution by using the maximum likelihood estimation and Bayesian estimation method via Lindley approximation method under Jeffreys prior and informative priors. The objective of this paper is to see which is the suitable prior for the shape and scale parameter of generalized Normal distribution. Simulation study with varying sample sizes, based on MSE, is conducted in R-software for data analysis.
Generalized Normal distribution, Newton-Raphson method, incomplete gamma function, joint posterior distribution, Fisher Information, Lindley approximation, Mean square error
Короткий адрес: https://sciup.org/15016677
IDR: 15016677 | DOI: 10.5815/ijmsc.2018.04.02
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