HIDDEN PERIODIC AUTOREGRESSIVE-MOVING AVERAGE MODELS IN TIME-SERIES DATA
成果类型：
Article
署名作者：
TIAO, GC; GRUPE, MR
署名单位：
Federal Reserve System - USA; Federal Reserve System Board of Governors
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/67.2.365
发表日期：
1980
页码：
365373
关键词：
摘要：
Some properties of a class of periodic models for characterizing seasonal time series are explored. The relationships between periodic models and multiple autoregressive-moving average models are developed, and used to gain insight into the behavior of periodic models. In particular it is shown how homogeneous autoregressive-moving average models may be mistakenly specified for series in which periodic properties are present. Consequences of such misspecification on forecasting and diagnostic checking are also derived. [Applicability to data on air pollution was discussed].
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