Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 463-477 |
| Number of pages | 15 |
| Journal | Australian & New Zealand Journal of Statistics |
| Volume | 42 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jan 2000 |
Keywords
- Autocorrelation
- Conditional residuals
- Generalized least squares
- Marginal residuals
- Mean shifts
- Model mis-specification
- Model transformation
- Orthogonal residuals
- Residual diagnostics
- Residual plots
- Time series regression