• Introduction.- Part I Recursive Estimation of Parameters in Linear Regression Models.- Recursive Estimation: A Simple Tutorial Introduction.- Recursive Least Squares Estimation.- Recursive Estimation of Time Variable Parameters in Regression Models.- Unobserved Component Models.- Part II Recursive Estimation of Parameters in Transfer Function Models.- Transfer Function Models and the Limitations of Recursive Least Squares.- Optimal Identification and Estimation of Discrete-Time Transfer Function Models.- Optimal Identification and Estimarization of Continuous-Time Transfer Function Models.- Identification of TF models in Closed-Loop.- Real-Time Recursive Parameter Estimation.- Part III Other Topics.- State-Dependent Parameter Estimation.- Data-Based Mechanistic (DBM) modeling.

From the book reviews: "This book is designed as an introductory reference and is written in an elegant and intuitive manner so as to enable students to understand such important and challenging topics as time series, system identification and recursive estimation methods. ... The book is highly recommended for the bookshelf of any student or practitioner who is beginning to deal with stochastic modelling, as well as for academics who need to explore methods beyond standard linear regressions for the process under study." (Juan R. Trapero, International Journal of Forecasting, October, 2014)