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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Bias-adjusted estimation in the ARX(1) model |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Computational Statistics and Data Analysis |
| Publisher | Elsevier |
| Geographical Reach | international |
| ISSN | 0167-9473 |
| Volume | 51 |
| Number | 7 |
| Page Range | 3355 - 3367 |
| Date | 2007 |
| Abstract Text | A new point estimator for the AR(1) coefficient in the linear regression model with arbitrary exogenous regressors and stationary AR(1) disturbances is developed. Its construction parallels that of the median--unbiased estimator, but uses the mode as a measure of central tendency. The mean--adjusted estimator is also considered, and saddlepoint approximations are used to lower the computational burden of all the estimators. Large--scale simulation studies for assessing their small--sample properties are conducted. Their relative performance depends almost exclusively on the value of the autoregressive parameter, with the new estimator dominating over a large part of the parameter space. |
| Digital Object Identifier | 10.1016/j.csda.2006.07.009 |
| Other Identification Number | merlin-id:588 |
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