CONVERGENCE OF LIMITING CASES OF CONTINUOUS-TIME, DISCRETE-SPACE JUMP PROCESSES TO DIFFUSION PROCESSES FOR BAYESIAN INFERENCE

Jump-diffusion algorithms are applied to sampling from Bayesian posterior distributions.We consider a class of random sampling algorithms based on continuous-time jump processes.The semigroup cartoon martian with big head theory of random processes lets us show that limiting cases read more of certain jump processes acting on discretized spaces con

This paper proposes one new design method for a higher order extended Kalman filter based on combining maximum correlation entropy with a Taylor network system to create a nonlinear random dynamic system with modeling errors and unknown statistical properties.Firstly, the transfer function and measurement function are transformed into a nonlinear r