Time Series Analysis: Forecasting And Control

Gwilym M. Jenkins

George E.P. Box

Gregory C. Reinsel

Wiley, John & Sons, Incorporated

Time Series Analysis

Wiley & Sons, Incorporated, John

Time Series Analysis: Forecasting and Control

Gerta M Ljung

Greta M Ljung

wiley

This book is concerned with the analysis of multivariate time series data. Such data might arise in business and economics, engineering, geophysical sciences, agriculture, and many other fields. The emphasis is on providing an account of the basic concepts and methods which are useful in analyzing such data, and includes a wide variety of examples drawn from many fields of application. The book presupposes a familiarity with univariate time series as might be gained from one semester of a graduate course, but it is otherwise self-contained. It covers the basic topics such as autocovariance matrices of stationary processes, vector ARMA models and their properties, forecasting ARMA processes, least squares and maximum likelihood estimation techniques for vector AR and ARMA models. In addition, it presents some more advanced topics and techniques including reduced rank structure, structural indices, scalar component models, canonical correlation analyses for vector time series, multivariate nonstationary unit root models and co-integration structure and state-space models and Kalman filtering techniques.

Elements of Multivariate Time Series Analysis (Springer Series in Statistics)

Business & Money

Economics

Springer

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