Forecasting Structural Time Series Models And The Kalman Filter
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Forecasting, Structural Time Series Models and the Kalman Filter
Author: Andrew C. Harvey
language: en
Publisher: Cambridge University Press
Release Date: 1990
A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.
Time Series Models
Author: Andrew C. Harvey
language: en
Publisher: Financial Times/Prentice Hall
Release Date: 1993
A companion volume to The Econometric Analysis of Time series, this book focuses on the estimation, testing and specification of dynamic models which are not based on any behavioural theory. It covers univariate and multivariate time series and emphasizes autoregressive moving-average processes.
Forecasting, Structural Time Series Models & the Kalman Filter
This book provides a synthesis of concepts and materials that ordinarily appear separately in time series and econometrics literature, presenting a comprehensive review of both theoretical and applied concepts. Perhaps the most novel feature of the book is its use of Kalman filtering together with econometric and time series methodology. From a technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. This technique was originally developed in control engineering but is becoming increasingly important in economics and operations research. The book is primarily concerned with modeling economic and social time series and with addressing the special problems that the treatment of such series pose.