The development of sophisticated computational methods for inference and forecasting has resulted in an enormous increase in the time series literature in recent years. This book integrates existing and new developments in time series analysis by presenting an overview of the main models and methods for inference and forecasting from the time-domain and frequency-domain perspectives, exploring connections between these two approaches. The book focuses on maximum likelihood and Bayesian methodologies.