Journal article
Asymptotic theory of outlier detection algorithms for linear time series regression models: Rejoinder
- Abstract:
-
Outlier detection algorithms are intimately connected with robust statistics that down-weight some observations to zero. We define a number of outlier detection algorithms related to the Huber-skip and least trimmed squares estimators, including the one-step Huber-skip estimator and the forward search. Next, we review a recently developed asymptotic theory of these. Finally, we analyse the gauge, the fraction of wrongly detected outliers, for a number of outlier detection algorithms and estab...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Bibliographic Details
- Publisher:
- Wiley Publisher's website
- Journal:
- Scandinavian Journal of Statistics: Theory and Applications Journal website
- Volume:
- 43
- Issue:
- 2
- Pages:
- 321–348
- Publication date:
- 2016-05-13
- Acceptance date:
- 2015-06-26
- DOI:
- ISSN:
-
1467-9469
Item Description
- Pubs id:
-
pubs:579190
- UUID:
-
uuid:3ff6fbe4-7687-4ad6-af01-ca2817ec7e40
- Local pid:
- pubs:579190
- Source identifiers:
-
579190
- Deposit date:
- 2015-12-09
Terms of use
- Copyright holder:
- Board of the Foundation of the Scandinavian Journal of Statistics
- Copyright date:
- 2016
- Notes:
- © 2016 Board of the Foundation of the Scandinavian Journal of Statistics. This is the accepted manuscript version of the article. The final version is available online from Wiley at: https://doi.org/10.1111/sjos.12174
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