Large Deviations with Diminishing Rates

Large Deviations with Diminishing Rates

The theory of large deviations for jump Markov processes has been generally proved only when jump rates are bounded below, away from zero (Dupuis and Ellis, 1995, The large deviations principle for a general class of queueing systems I. Trans. Amer. Math. Soc. 347 2689–2751; Ignatiouk-Robert, 2002, Sample path large deviations and convergence parameters. Ann. Appl. Probab. 11 1292–1329; Shwartz...

Large Deviations with Diminishing Rate

The theory of large deviations for jump Markov processes has been generally proved only when jump rates are bounded below, away from zero [4, 8, 12]. Yet various applications of interest do not satisfy this condition. We describe several classes of models where jump rates diminish to zero in a Lipschitz continuous way. Under appropriate conditions, we prove that the sample path large deviations...

Large Deviations Rates for Distributed Inference

This thesis analyzes large deviations performance of linear consensus-based algorithms for distributed inference (detection and estimation). With consensus-based algorithms, agents communicate locally with their neighbors, through intermittently failing links, and assimilate their streaming observations in real time. While existing work usually focuses on asymptotic consistency and asymptotic n...

From Rates of Mixing to Recurrence times via Large Deviations

A classic approach in dynamical systems is to use particular geometric structures to deduce statistical properties, for example the existence of invariant measures with stochastic-like behaviour such as large deviations or decay of correlations. Such geometric structures are generally highly non-trivial and thus a natural question is the extent to which this approach can be applied. In this pap...

Large Deviations