An Introduction to Bayesian Inference in Process Monitoring, Control and Optimization

ABSTRACT We present in this first chapter a general overview of Bayesian inference. A brief account of the fundaments is given, after which we focus on the following problems: inference in normally distributed data (univariate and multivariate), Kalman filtering, and Bayesian linear regression. Applications are noted in process monitoring, control, and optimization. Whenever appropriate, we refer to all subsequent chapters in this book.