The Noise Component:N(at)

Abstract

Chapter 3 develops the methods or strategies for building ARIMA noise models. At one level, the iterative identify-estimate-diagnose modeling strategy proposed by Box and Jenkins has changed little. At another level, the collective experience of time series experimenters leads to several modifications of the strategy. For the most part, these changes are aimed at solving practical problems. Compared to the 1970s, for example, modelers today pay more attention to transformations and to the usefulness and interpretability of an ARIMA model. The Box-Jenkins ARIMA noise modeling strategy is illustrated with detailed analyses of twelve time series. The example analyses include non-Normal time series, stationary white noise, autoregressive and moving average time series, nonstationary time series, and seasonal time series. The time series models build in Chapter 3 are re-introduced in later chapters.