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A new procedure : bayesian selection to find the best of geometric population under general loss function
Author
Source
Journal of Kufa for Mathematics and Computer
Issue
Vol. 1, Issue 6 (31 Dec. 2012), pp.49-56, 8 p.
Publisher
University of Kufa Faculty of Mathematics and Computers Science
Publication Date
2012-12-31
Country of Publication
Iraq
No. of Pages
8
Main Subjects
Abstract EN
In many practical situations the experimenter is confronted with the problem of choosing the best one of a number of populations or categories or ranking them according to their performance.
This paper derives a procedure for selecting the better of Two Geometric populations employing a decision-theoretic Bayesian framework with Beta prior under general loss function.
The numerical results for this procedure are given by using Math Works Matlab ver 7.0.1 with different loss functions constant, linear and quadratic, where in one equation we can obtain the Bayes risk for the three types of the loss functions : constant, linear and quadratic.
American Psychological Association (APA)
Hathut, Samira Faysal. 2012. A new procedure : bayesian selection to find the best of geometric population under general loss function. Journal of Kufa for Mathematics and Computer،Vol. 1, no. 6, pp.49-56.
https://search.emarefa.net/detail/BIM-317900
Modern Language Association (MLA)
Hathut, Samira Faysal. A new procedure : bayesian selection to find the best of geometric population under general loss function. Journal of Kufa for Mathematics and Computer Vol. 1, no. 6 (Dec. 2012), pp.49-56.
https://search.emarefa.net/detail/BIM-317900
American Medical Association (AMA)
Hathut, Samira Faysal. A new procedure : bayesian selection to find the best of geometric population under general loss function. Journal of Kufa for Mathematics and Computer. 2012. Vol. 1, no. 6, pp.49-56.
https://search.emarefa.net/detail/BIM-317900
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 56
Record ID
BIM-317900