Methods of Environmental Data Analysis by A. C. Bajpai, Irene M. Calus, J. A. Fairley (auth.), C. N. PDF

By A. C. Bajpai, Irene M. Calus, J. A. Fairley (auth.), C. N. Hewitt (eds.)

ISBN-10: 0412739909

ISBN-13: 9780412739903

ISBN-10: 9401129207

ISBN-13: 9789401129206

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Example text

The kinds of nonstationarity and/or nonlinearity observed in the three series shown in Fig. I are indicative of changes in the underlying statistical characteristics ofthe data. As a result, we might expect that any mathematical models used to characterise these data should be able to represent this nonstationarity or nonlinearity if they are to characterise the time-series in an acceptable manner. Box & Jenkins,2 amongst many other statisticians, have recognised this problem and have proposed various methods of tackling it.

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.

This is now regarded as the stem. For the other groups the stems are thus 5, 6, etc. All observations in a particular group have the same stem. The remaining part of an observation, which varies within the group, is the leaf Thus 68 and 62 have the same stem, 6, but their leaves are 8 and 2 respectively. The way that the stem and its leaves are displayed is shown in Table 8. If desired a column giving the frequencies can be shown alongside the display. In the present example, the stem represented 'tens' and the leaf 'units'.

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Methods of Environmental Data Analysis by A. C. Bajpai, Irene M. Calus, J. A. Fairley (auth.), C. N. Hewitt (eds.)


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