Breakdown point theory for implied probability bootstrap
This paper studies robustness of bootstrap inference methods under moment conditions. In particular, we compare the uniform weight and implied probability bootstraps by analyzing behaviors of the bootstrap quantiles when outliers take arbitrarily large values, and derive the breakdown points for those bootstrap quantiles. The breakdown point properties characterize the situation where the implied probability bootstrap is more robust than the uniform weight bootstrap against outliers. Simulation studies illustrate our theoretical findings.
(This abstract was borrowed from another version of this item.)
Volume (Year): 15 (2012)
Issue (Month): 1 (02)
|Contact details of provider:|| Postal: 2 Dean Trench Street, Westminster, SW1P 3HE|
Phone: +44 20 3137 6301
Web page: http://www.res.org.uk/
More information through EDIRC
|Order Information:||Web: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1368-423X|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Matías Salibián-Barrera & Stefan Aelst & Gert Willems, 2008. "Fast and robust bootstrap," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(1), pages 41-71, February.