Environmetric Methods of Nonstationary Time-Series Analysis: Univariate Methods

By ‘environmetrics’, we mean the application of statistical and systems methods to the analysis and modelling of environmental data. In this chapter, we consider a particular class of environmetric methods; namely the analysis of environmental time-series. Although such time-series can be obtained from planned experiments, they are more often obtained by passively monitoring the environmental variables over long periods of time. Not surprisingly, therefore, the statistical characteristics of such series can change considerably over the observation interval, so that the series can be considered nonstationary in a statistical sense. Figure 1(a), for example, shows a topical and important environmental time-series—the variations of atmospheric CO2 measured at Mauna Loa in Hawaii over the period 1974 to 1987. This series exhibits a clear upward trend, together with pronounced annual periodicity. The trend behaviour is a classic example of statistical nonstationarity of the mean, with the local mean value of the series changing markedly over the observation interval.

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