Time series analysis: forecasting and control rev. ed.

Abstract

This text is divided into 4 parts: 1) stochastic models and their forecasting 2) stochastic model building 3) transfer function model building and 4) design of discrete control schemes. The book presents methods for building identifying fitting and checking models for time series and dynamic systems. Methods discussed are appropriate for discrete (sampled-data) systems where observation of the system and an opportunity to take control action occur at equally spaced intervals of time. These time series and dynamic models are illustrated in 3 important areas of application: 1) the forecasting of future values of a time series from current and past values; 2) the determination of the transfer function of a system--the determination of a dynamic input-output model that can show the effect on the output of a system subject to inertia of any given series of inputs; and 3) the design of simple feed forward and feedback control schemes by means of which potential deviations of the system output from a desired target may be compensated so far as possible.