Exponential Change of Measure for General Piecewise Deterministic Markov Processes

Abstract

We consider a general piecewise deterministic Markov process (PDMP) $X=\{X_t{\}}_{t⩾0}$ with measure-valued generator $\mathcal{A}$, for which the conditional distribution function of the inter-occurrence time is not necessarily absolutely continuous. A general form of the exponential martingales is presented as $$M_t^f=\frac{f(X_t)}{f(X_0)}{\left[\mathrm{Sexp}\left({\int }_{(0,t]}\frac{\mathrm{d}L(\mathcal{A}f{)}_s}{f(X_{s-})}\right)\right]}^{-1}.$$ Using this exponential martingale as a likelihood ratio process, we define a new probability measure. It is shown that the original process remains a general PDMP under the new probability measure. And we find the new measure-valued generator and its domain.

References in corpus (2)

• Nonequilibrium Markov processes conditioned on large deviations
• Measure-Valued Generators of General Piecewise Deterministic Markov Processes