Jackknife-after-bootstrap regression influence diagnostics

Michael Martin and Steven Roberts

Journal of Nonparametric Statistics, 2010, vol. 22, issue 2, 257-269

Abstract: We propose a bootstrap approach to gauging the size of regression influence measures. The bootstrap cut-offs generated are based on approximating the sampling distribution of the respective measures under resampling, work well for small samples, and allow for features such as asymmetric cut-offs. The bootstrap method uses Efron's jackknife-after-bootstrap idea to deal with the issue of an influential point contaminating the resamples from which cut-offs are calculated. The method is illustrated through both real-world examples and a simulation study, the results of which suggest that the bootstrap method provides a reliable alternative to traditional methods particularly in small to moderate samples.

Date: 2010
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Citations: View citations in EconPapers (4)

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DOI: 10.1080/10485250903287906

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