In this paper, the largest and the smallest observations are considered, at the time when a new record of either kind (upper or lower) occurs based on a sequence of independent random variables with identical continuous distributions. We prove that sequences of the residual or past entropy of the current records characterizes F in the family of continuous distributions. The exponential and the ...

Generalized Pareto distribution play an important role in reliability, extreme value theory, and other branches of applied probability and statistics. This family of distributions includes exponential distribution, Pareto distribution, and Power distribution. In this paper, we established exact expressions and recurrence relations satisfied by the quotient moments of generalized order statistic...

A possible explanation for the frequent occurrence of power-law distributions in biology and elsewhere comes from an analysis of the interplay between random time evolution and random observation or killing time. If the system population or its topological parameters grow exponentially with time, and observations on the system correspond to stopping the evolution at an exponentially distributed...

We investigate the structure of the global maximizers of stochas-tic interdependence, which is measured by the Kullback-Leibler divergence of the underlying joint probability distribution from the exponential family of factorizable random fields (multi-information). As a consequence of our structure results, it comes out that random fields with globally maximal multi-information are contained i...

We show that the variance of the Monte Carlo estimator that is importance sampled from an exponential family is a convex function of the natural parameter of the distribution. With this insight, we propose an adaptive importance sampling algorithm that simultaneously improves the choice of sampling distribution while accumulating a Monte Carlo estimate. Exploiting convexity, we prove that the m...