Comparison of Two Information Structures with Noise and Its Application to Bayes Decision Analysis
Cunhua Qian, Jing Chen, Toshio Nakagawa · Quality Technology & Quantitative Management · 2009
In order to raise the efficiency of Bayesian decision analysis, the comparison analysis of added information structure with noise are considered by using the correlation coefficient between two information structures. The entropy measures the indefiniteness of information system in information theory. Using the conditional entropy, we define the decrease of object’s uncertainty, and measure the volume of information content in the added information structures. An expression about correlation coefficient between two information structures is derived by considering the standardization of information content. Numerical illustrations are also presented. Such an analysis demonstrates that the correlation coefficient can be used to compare and appraise information structures with noise.