Bayes estimation under balanced loss functions

Other Title(s)

تقدير بايز بموجب وظائف الخسارة المتوازنة

Author

al-Badran, al-Firas Munthir

Source

The Journal of Administration and Economics

Issue

Vol. 42, Issue 119 (30 Apr. 2019), pp.108-120, 13 p.

Publisher

al-Mustansiriyah University College of Management and Economic

Publication Date

2019-04-30

Country of Publication

Iraq

No. of Pages

13

Main Subjects

Business Administration
Economy and Commerce

Topics

Abstract EN

In this research, the researcher has derived different standard Bayes estimators for scale parameter of Exponential distribution by using balanced and unbalanced loss function.

This estimation includes two cases availability and lack of primary information (Jeffery and Gamma conjugate priors) about the phenomenon studied.

Simulation experiments with different sample sizes and virtual parameters have been built for this purpose, then a comparison is mads between these estimators depend on the Mean Square Error (MSE) criteria.

The results have demonstrating the superiority of balanced loss functions in the ence of prior information about the phenomenon studied, while they may not have the same efficiency if availability of prior information about this phenomenon is cannot found.

American Psychological Association (APA)

al-Badran, al-Firas Munthir. 2019. Bayes estimation under balanced loss functions. The Journal of Administration and Economics،Vol. 42, no. 119, pp.108-120.
https://search.emarefa.net/detail/BIM-1092158

Modern Language Association (MLA)

al-Badran, al-Firas Munthir. Bayes estimation under balanced loss functions. The Journal of Administration and Economics Vol. 42, no. 119 (2019), pp.108-120.
https://search.emarefa.net/detail/BIM-1092158

American Medical Association (AMA)

al-Badran, al-Firas Munthir. Bayes estimation under balanced loss functions. The Journal of Administration and Economics. 2019. Vol. 42, no. 119, pp.108-120.
https://search.emarefa.net/detail/BIM-1092158

Data Type

Journal Articles

Language

English

Notes

-

Record ID

BIM-1092158