Not logged in.
Quick Search - Contribution
Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Autoregressive Lag-Order Selection Using Conditional Saddlepoint Approximations |
| Organization Unit | |
| Authors |
|
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
|
| Journal Title | Econometrics |
| Publisher | MDPI Publishing |
| Geographical Reach | international |
| ISSN | 2225-1146 |
| Volume | 5 |
| Number | 3 |
| Page Range | 43 |
| Date | 2017 |
| Abstract Text | A new method for determining the lag order of the autoregressive polynomial in regression models with autocorrelated normal disturbances is proposed. It is based on a sequential testing procedure using conditional saddlepoint approximations and permits the desire for parsimony to be explicitly incorporated, unlike penalty-based model selection methods. Extensive simulation results indicate that the new method is usually competitive with, and often better than, common model selection methods. |
| Free access at | DOI |
| Related URLs |
|
| Digital Object Identifier | 10.3390/econometrics5030043 |
| Other Identification Number | merlin-id:15387 |
| PDF File |
Download from ZORA
|
| Export |
BibTeX
EP3 XML (ZORA)
|