EconPapers    
Economics at your fingertips  
 

Identification of outlier bootstrap samples

J. Munoz-Garcia, R. Pino-Mejias, J. M. Munoz-Pichardo and M. D. Cubiles-De-La-Vega

Journal of Applied Statistics, 1997, vol. 24, issue 3, 333-342

Abstract: We define a variation of Efron's method II based on the outlier bootstrap sample concept. A criterion for the identification of such samples is given, with which a variation in the bootstrap sample generation algorithm is introduced. The results of several simulations are analyzed in which, in comparison with Efron's method II, a higher degree of closeness to the estimated quantities can be observed.

Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664769723729 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:24:y:1997:i:3:p:333-342

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664769723729

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:japsta:v:24:y:1997:i:3:p:333-342