Investigation of the method of sequential analysis of Bayesian type
Journal Title: JOURNAL OF ADVANCES IN MATHEMATICS - Year 2014, Vol 7, Issue 3
Abstract
The results of investigation of the properties of new sequential methods of testing many hypotheses based on special properties of hypotheses acceptance regions in the constrained Bayesian tasks of testing many hypotheses are offered. In particular, some relations between the errors of the first and the second kinds in constrained Bayesian task and in sequential method of Bayesian type depending on the divergence between the tested hypotheses are given. Also dependences of the Lagrange multiplier and the risk function on the probability of incorrectly accepted hypotheses are presented. Theses results are necessary for computation of errors of made decisions at testing multiple hypotheses using offered new sequential methods of testing hypotheses. Computation results of some examples confirm the rightness of theoretical researches.
Authors and Affiliations
Kartlos Joseph Kachiashvili
Fuzzy decision making in Business intelligence in the context of Gilgit-Baltistan
The main purpose of this paper is to investigate and implement fuzzy decision based on unequal objectives and minimization of regret for the decision making in the business intelligence and to compare the weight of produ...
Approximation of General Form for a Sequence of Linear Positive Operators Based on Four Parameters
In the present paper, we define a generalization sequence of linear positive operators based on four parameters which is reduce to many other sequences of summation–integral older type operators of any weight function (B...
Some Techniques to Compute Multiplicative Inverses for Advanced Encryption Standard
This paper gives some techniques to compute the set of multiplicative inverses, which uses in the Advanced Encryption Standard (AES).
Adomian Decomposition Method of Fredholm Integral Equation of the Second kind Using Maple
In this paper, we will be find exact solution of Fredholm Integral equation of the second kind through using Adomian Decomposition Method by using Maple 17 program, then we found that exact solution.
Markov Stochastic Processes in Biology and Mathematics -- the Same, and yet Different
Virtually every biological model utilising a random number generator is a Markov stochastic process. Numerical simulations of such processes are performed using stochastic or intensity matrices or kernels. Biologists, ho...