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Abstract

In the chapter on stochastic processes the Poisson process was introduced as an example of an RCLL nonexplosive counting process. Furthermore, we reviewed a general theory of counting processes as point processes on the real line within the framework of martingale theory and dynamics. Indeed, for these processes, under the usual regularity assumptions, we can invoke the Doob-Meyer decomposition theorem (see (2.79) onwards) and claim that any nonexplosive RCLL process \( \left( {X_t } \right)t \in \mathbb{R}_ + \) satisfies a generalized stochastic differential equation of the form dXt = dAt + dMt (6.1) subject to a suitable initial condition. Here A is the compensator of the process representing the model of “evolution” and M is a martingale representing the “noise.”

Keywords

Epidemic Model Empirical Process Counting Process Probability Generate Function Kernel Versus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Birkhäuser Boston 2005

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