Abstract
The autocorrelation function, ACF, is an important guide to the properties of a time series. Explicit equations are derived for ACF in the presence of heteroscedasticity disturbances in pth order autoregressive, AR(p), processes. Two cases are presented: (1) when the disturbance term follows the general covariance matrix, σ , and (2) when the diagonal elements of S are not all identical but σi,j = 0 ∀i j.
| Original language | English |
|---|---|
| Pages (from-to) | 625-631 |
| Number of pages | 7 |
| Journal | Journal of Modern Applied Statistical Methods |
| Volume | 10 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
Keywords
- Autocorrelation
- Autoregressive
- Covariance
- Disturbance
- Heteroscedasticity
- Homoscedasticity
- Time series
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty