Time Series Modeling,Spectral Analysis,and Forecasting.

摘要

A strategy for building models for an observed time series is presented in this paper. We seek to fit time domain models which can be interpreted in terms of trend and seasonal components, provide forecasts, and provide spectral estimators. Our time series modeling strategy attempts to achieve a distribution function. The approach described could be called: the autoregressive spectral method for time domain model identification of non-stationary time series (which could be abbreviated AR-SPECTRAL-TIME-ID). (Author)