Title :
Determining the independence of random variables
Author :
Massey, James L.
Author_Institution :
Signal & Inf. Process. Lab., Swiss Federal Inst. of Technol., Zurich, Switzerland
Abstract :
A graphical calculus is presented for determining the independence and conditional independence of random variables in a specified probabilistic setting. The calculus is developed first for the case of random variables that form a Markov chain. The calculus is then extended to the “general causal case” where the random variables are obtained from a sequence of random experiments in which each experiment can be carried out in full when the results of specified previous experiments are made available to it
Keywords :
Markov processes; calculus; graph theory; information theory; probability; random processes; Markov chain; conditional independence; general causal case; graphical calculus; independence; information theory; probabilistic dependence; random experiments; random variables; Calculus; Information theory; Mutual information; Random variables;
Conference_Titel :
Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
Conference_Location :
Whistler, BC
Print_ISBN :
0-7803-2453-6
DOI :
10.1109/ISIT.1995.531113
