State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developme

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare,

The book blends readability and accessibility common to undergraduate control systems texts with the mathematical rigor necessary to form a solid theoretical fo

model's predictive capability? These are some of the questions that need to be answered in proposing any time series model construction method. This book addres

Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space