Search

By combining a bound on the absolute value of the difference of mutual information between two joint probablity distributions with a fixed variational distance, and a bound on the probability of a maximal deviation in variational distance between a true joint probability distribution and an empirical joint probability distribution, confidence intervals for the mutual information of two random variables with finite alphabets are established. Different from previous results, these intervals do not need any assumptions on the distribution and the sample size., Comment: 5 pages, 2 figure

In this paper a numerical method is presented, which finds a lower bound for the mutual information between a binary and an arbitrary finite random variable with joint distributions that have a variational distance not greater than a known value to a known joint distribution. This lower bound can be applied to mutual information estimation with confidence intervals., Comment: 4 pages, 3 figures