Distribution of Mutual Information from Complete and Incomplete Data
Mutual information is widely used, in a descriptive way, to measure the stochastic dependence of categorical random variables. In order to address questions such as the reliability of the descriptive value, one must consider sample-to-population inferential approaches. This paper deals with the posterior distribution of mutual information, as obtained in a Bayesian framework by a second-order Dirichlet prior distribution. The exact analytical expression for the mean, and analytical...[Show more]
|Collections||ANU Research Publications|
|Source:||Computational Statistics and Data Analysis|
|01_Hutter_Distribution_of_Mutual_2005.pdf||335.83 kB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.