Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations
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 incor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-09-01
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| Series: | Econometrics |
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| Online Access: | https://www.mdpi.com/2225-1146/5/3/43 |
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Article |
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doaj-95604518cacf4ef097bb7b6e74790eb02020-11-25T01:01:31ZengMDPI AGEconometrics2225-11462017-09-01534310.3390/econometrics5030043econometrics5030043Autoregressive Lag—Order Selection Using Conditional Saddlepoint ApproximationsRonald W. Butler0Marc S. Paolella1Department of Statistical Science, Southern Methodist University, Dallas, TX 75275-0332, USADepartment of Banking and Finance, University of Zurich, Zurich 8032, SwitzerlandA 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.https://www.mdpi.com/2225-1146/5/3/43ARMAsaddlepoint approximationsimplicity |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Ronald W. Butler Marc S. Paolella |
| spellingShingle |
Ronald W. Butler Marc S. Paolella Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations Econometrics ARMA saddlepoint approximation simplicity |
| author_facet |
Ronald W. Butler Marc S. Paolella |
| author_sort |
Ronald W. Butler |
| title |
Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations |
| title_short |
Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations |
| title_full |
Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations |
| title_fullStr |
Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations |
| title_full_unstemmed |
Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations |
| title_sort |
autoregressive lag—order selection using conditional saddlepoint approximations |
| publisher |
MDPI AG |
| series |
Econometrics |
| issn |
2225-1146 |
| publishDate |
2017-09-01 |
| description |
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. |
| topic |
ARMA saddlepoint approximation simplicity |
| url |
https://www.mdpi.com/2225-1146/5/3/43 |
| work_keys_str_mv |
AT ronaldwbutler autoregressivelagorderselectionusingconditionalsaddlepointapproximations AT marcspaolella autoregressivelagorderselectionusingconditionalsaddlepointapproximations |
| _version_ |
1725208878233157632 |