Sequential Bayesian Estimation
摘要
This chapter presents Monte-Carlo Markov Chain methods and connected topics, namely Importance Sampling, Metropolis-Hastings Algorithm, Kalman Filtering, Particle Filtering, and Bayesian Optimization. The use of UQ for the determination of the distribution of the noise is presented. Programs in R implement all the topics introduced, with examples of use.