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Theory & Methods: Residual Diagnostic Plots for Checking for Model Mis‐specification in Time Series Regression
Author(s) -
Fraccaro Richard,
Hyndman Rob J.,
Veevers Alan
Publication year - 2000
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00142
Subject(s) - mathematics , residual , outlier , statistics , studentized residual , series (stratigraphy) , regression , regression analysis , autocorrelation , econometrics , algorithm , paleontology , biology
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.