variance measure and also the relative entropy minimizer have been developed in the literature. This project focuses on the …-dimensional Brownian motion. We apply Girsanov transforms to determine the relative entropy minimizer and the associated minimum martingale …

denominated in entropy which is a measure of uncertainty and is a function of probabilities only. Mutual information is defined as … the reduction of entropy when an information source X is available. We state that the log of one plus the accounting rate … reduction of classical or Shannon entropy. If all possible states of the world are observable (and contractible), then all …

I entertain a generalization of the standard Bolzmann-Gibbs-Shannon measure of entropy in multiplier preferences of …

aggregate measures of seat/vote disproportionality of the generalized entropy family: using a divisor method based upon such a … generalized logarithmic mean coincides with minimizing a generalized entropy inequality measure. The Balinski-Young 'favoring … small states' - ordering ranks the generalized entropy methods. This framework improves upon an inconsistency in the …

We present in this paper the application of a cross entropy method (CEM) to the vehicle routing problem (VRP). The CEM …

The cross entropy method (CEM) is a relatively new stochastic metaheuristic, initially developed to estimate rare event …

constituent variables can be arranged so as to yield some generalized maximum entropy synthetic indicators that represent the …

The Cross Entropy method is a well-known adaptive importance sampling method for rare-event probability estimation … version of the Cross Entropy method frequently yields efficient estimators. We illustrate the excellent practical performance …

In the existing financial literature, entropy based ideas have been proposed in portfolio optimization and in model … distributions ubiquitous in financial practice. We note that this drawback may be corrected if 'polynomial-divergence' entropy …