Study Relative Loss Values ​​for Entropy Functions of Lindley and Truncated Lindley Distributions

Abstract

Entropy is a measure of uncertainty in probability distributions when studying different phenomena. Numerical comparisons of the relative loss in entropy are calculated to determine which entropy measure has better advantages over the other. In this paper, five entropy measures are derived for the Lindley and truncated Lindley distributions to calculate the relative loss of entropy of the two distributions when the underlying probability distribution is the truncated Lindley distribution instead of the Lindley distribution, and to determine the best uncertainty measure based on the relative loss results.