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An ARIMA-Model-Based Approach to Seasonal Adjustment

 

作者: S.C. Hillmer,   G.C. Tiao,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1982）
卷期: Volume 77, issue 377  

页码: 63-70

 

ISSN:0162-1459

 

年代: 1982

 

DOI:10.1080/01621459.1982.10477767

 

出版商: Taylor & Francis Group

 

关键词: ARIMA model;Seasonal adjustment;Census X-11 program;Pseudospectral density function;Model-based decomposition;Canonical decomposition

 

数据来源: Taylor

 

摘要:

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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