Bayesian Methods and Simulation Techniques
Purpose Here, we present a general methodology for solving problems of filtering, smoothing, and prediction, along with that of identifying transfer functions. For this, we use a Bayesian approach, which allows possible a priori information about the desired parameters to be incorporated. In order to be able to perform the numerical computation of the estimators, we use Monte Carlo techniques to solve integration and maximisation problems that appear in Bayesian estimation.
KeywordsMarkov Chain Probability Density Function Monte Carlo Markov Chain Bayesian Method Simulation Technique
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