Application Bayesian Approach in Tasks Decision-Making Support

Aliyeva Tarana Abulfaz^1,

¹Department of Information Economic and Technology, Azerbaijan State Economic University, Baku, Azerbaijan

Cite this paper

Aliyeva Tarana Abulfaz. Application Bayesian Approach in Tasks Decision-Making Support. American Journal of Applied Mathematics and Statistics. 2015; 3(6):257-262. doi: 10.12691/AJAMS-3-6-7

Abstract

The proposed work is devoted to the use of the Bayesian approach based on probabilistic method of use, along with the original statistical data prior information about the current process. Especially significant advantages over classical methods in terms of the accuracy of the statistical inference Bayesian approach is in the relatively small samples, which is very characteristic of the simulation. A theorem on minimizing classification error probability is proved. About choosing a priori distribution parameters from the coordinated class of distributions is considered.

Keywords

a priori distribution, a posteriori distribution, a coordinated distribution, Bayesian approach

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]	Tulupyev, A.L., Nikolenko S.I., Sirotkin A.V., BAYESIAN NETWORKS: A Probabilistic Logic Approach (Russian), St. Petersburg: Nauka, 2006. 607 p.
[2]	Morris, U.T, The science of management: A Bayesian approach.. М: Мir, 1971. 304 p.
[3]	Friedrich Schreiber, Probability and Bayesian Statistics Plenum Press, The Extended Bayes-Postulate, Its Potential Effect on Statistical methods and Some Historical Aspects, New York, 1987, pp. 423-430.
[4]	Jeffreys, Scientific Inference. 2nd ed. Cambridge University Press, 1957.
[5]	De Groot M.H. Optimal Statistical Decisions: Wiley, 2004.