Filter design for the seasonal adjustment of a time series
Edward L. Melnick, John Moussourakis · Communications in Statistics · 1974
Studying the fluctuations of a time series is made easier if the seasonal component is eliminated. This paper describes a new approach to seasonal adjustment which not only considers the effect of the seasonal variation upon the observed phenomena, but also the relationship between the desired accuracy of the adjust¬ment and its resulting properties. An algorithm is presented which develops moving average filters for seasonally adjusting the data. The output of the algorithm is discussed in terms of criteria proposed for evaluating seasonal adjustments.