Higher order asymptotics for large deviations — Part II

Asymptotics of Higher Order Entropies

Higher order entropies are kinetic entropy estimators for fluid models. These quantities are quadratic in the velocity v and temperature T derivatives and have temperature dependent coefficients. We investigate asymptotic expansions of higher order entropies for incompressible flows in terms of the Knudsen ǫk and Mach ǫm numbers. The correspoding entropic inequalities are obtained when ‖ log T‖...

Higher-order asymptotics for the parametric complexity

The parametric complexity is the key quantity in the minimum description length (MDL) approach to statistical model selection. Rissanen and others have shown that the parametric complexity of a statistical model approaches a simple function of the Fisher information volume of the model as the sample size n goes to infinity. This paper derives higher-order asymptotic expansions for the parametri...

Refined large deviations asymptotics for Markov-modulated infinite-server systems

Many networking-related settings can be modeled by Markov-modulated infinite-server systems. In such models, the customers’ arrival rates and service rates are modulated by a Markovian background process; additionally, there are infinitely many servers (and consequently the resulting model is often used as a proxy for the corresponding many-server model). The Markov-modulated infinite-server mo...

Large Deviations and Exact Asymptotics for Constrained Exponential Random Graphs

Sample Path Large Deviations for Order Statistics

We consider the sample paths of the order statistics of independent and identically distributed random variables with common distribution function F . If F is strictly increasing but possibly having discontinuities, we prove that the sample paths of the order statistics satisfy the large deviation principle in the Skorokhod M1 topology. Sanov’s theorem is deduced in the SkorokhodM ′ 1 topology ...