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Journal of the American Statistical Association Volume 77, 1982 - Issue 377
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Theory and Method

An ARIMA-Model-Based Approach to Seasonal Adjustment

S. C. Hillmer School of Business, University of Kansas, Lawrence, KS, 66044, USA
&
G. C. Tiao Department of Statistics, University of Wisconsin, Madison, WI, 53706, USA
Pages 63-70 | Received 01 Oct 1980, Published online: 12 Mar 2012
 
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Abstract

This article proposes a model-based procedure to decompose a time series uniquely into mutually independent additive seasonal, trend, and irregular noise components. The series is assumed to follow the Gaussian ARIMA model. Properties of the procedure are discussed and an actual example is given.

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