Parameter estimation for a class of stochastic hybrid systems with state-dependent switching noise

In this paper, we study a class of stochastic hybrid systems with piecewise linear partitioned state space, and state-depending switching governed by an intensity function. Using maximum likelihood methods, we develop a method for estimating parameters of switching distributions in such systems. This is accomplished by identifying the trajectories of a stochastic hybrid system with a point process. The efficiency of the findings are demonstrated on an example.