Time Series Analysis - Classical Seasonal Decomposition (Census Method 1)

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Classical Seasonal Decomposition (Census Method 1) - General Introduction
Suppose you recorded the monthly passenger load on international flights for a period of 12 years (such data are included in the example datafile Series_G.sta, see also Box & Jenkins, 1976). If you plot those data, it is apparent that (1) there appears to be a linear upwards trend in the passenger loads over the years, and (2) there is a recurring pattern or seasonality within each year (i.e., most travel occurs during the summer months, and a minor peak occurs during the December holidays). The purpose of the seasonal decomposition method is to isolate those components, that is, to de-compose the series into the trend effect, seasonal effects, and remaining variability. The "classic" technique designed to accomplish this decomposition is known as the Census I method. This technique is described and discussed in detail in Makridakis, Wheelwright, and McGee (1983), and Makridakis and Wheelwright (1989).
Ratios-to-Moving Averages Classical Seasonal Decomposition (Census Method I)