Residual diagnostic plots for checking for model mis-specification in time series regression

被引:13
作者
Fraccaro, R [1 ]
Hyndman, RJ
Veevers, A
机构
[1] Monash Univ, Dept Econometr & Business Stat, Clayton, Vic 3168, Australia
[2] CSIRO, Math & Informat Sci, Clayton, Vic 3168, Australia
关键词
autocorrelation; conditional residuals; generalized least squares; marginal residuals; mean shifts; model mis-specification; model transformation; orthogonal residuals; residual diagnostics; residual plots; time series regression;
D O I
10.1111/1467-842X.00142
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper considers residuals for time series regression. Despite much literature on visual diagnostics for uncorrelated data, there is little on the autocorrelated case. To examine various aspects of the fitted time series regression model, three residuals are considered. The fitted regression model can be checked using orthogonal residuals; the time series error model can be analysed using marginal residuals; and the white noise error component can be tested using conditional residuals. When used together, these residuals allow identification of outliers, model mis-specification and mean shifts. Due to the sensitivity of conditional residuals to model mis-specification, it is suggested that the orthogonal and marginal residuals be examined first.
引用
收藏
页码:463 / 477
页数:15
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