Bayesian Inference for Continuous-Time ARMA Models Driven by Jump Diffusions

@article{Yang2007BayesianIF,
  title={Bayesian Inference for Continuous-Time ARMA Models Driven by Jump Diffusions},
  author={Gary Yang and Simon J. Godsill},
  journal={2007 IEEE/SP 14th Workshop on Statistical Signal Processing},
  year={2007},
  pages={99-103}
}
This paper investigates the problem of Bayesian parameter estimation for continuous-time autoregressive moving average (CARMA) models driven by jump diffusions. Inference is performed through the evaluation of the likelihood function conditional on jump times, and the realized jump sizes are marginalized assuming they are normally distributed. A Markov chain Monte Carlo (MCMC) algorithm is then developed to explore the parameter space based on the conditional likelihood and an assumed prior… CONTINUE READING