Bayesian estimation for two parameters of gamma distribution under precautionary loss function

Source

Ibn al-Haitham Journal for Pure and Applied Science

Issue

Vol. 32, Issue 1 (30 Apr. 2019), pp.187-196, 10 p.

Publisher

University of Baghdad College of Education for Pure Science / Ibn al-Haitham

Publication Date

2019-04-30

Country of Publication

Iraq

No. of Pages

10

Main Subjects

Mathematics

Topics

Abstract EN

In the current study, the researchers have been obtained bayes estimators for the shape and scale parameters of gamma distribution under the precautionary loss function, assuming the priors, represented by gamma and exponential priors for the shape and scale parameters respectively.

moment, maximum likelihood estimators and lindley’s approximation have been used effectively in bayesian estimation.

based on monte carlo simulation method, those estimators are compared depending on the mean squared errors (mse’s).

the results show that, the performance of bayes estimator under precautionary loss function with gamma and exponential priors is better than other estimates in all cases.

American Psychological Association (APA)

Naji, Luayy F.& Rashid, Huda A.. 2019. Bayesian estimation for two parameters of gamma distribution under precautionary loss function. Ibn al-Haitham Journal for Pure and Applied Science،Vol. 32, no. 1, pp.187-196.
https://search.emarefa.net/detail/BIM-898143

Modern Language Association (MLA)

Naji, Luayy F.& Rashid, Huda A.. Bayesian estimation for two parameters of gamma distribution under precautionary loss function. Ibn al-Haitham Journal for Pure and Applied Science Vol. 32, no. 1 (2019), pp.187-196.
https://search.emarefa.net/detail/BIM-898143

American Medical Association (AMA)

Naji, Luayy F.& Rashid, Huda A.. Bayesian estimation for two parameters of gamma distribution under precautionary loss function. Ibn al-Haitham Journal for Pure and Applied Science. 2019. Vol. 32, no. 1, pp.187-196.
https://search.emarefa.net/detail/BIM-898143

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 196

Record ID

BIM-898143