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One Sided Crossvalidation for Density Estimation

Miranda, M. D. M., Nielsen, J. P. and Sperlich, S. (2009). One Sided Crossvalidation for Density Estimation. In: Gregoriou, G.N. (Ed.), Operational Risk Towards Basel III: Best Practices and Issues in Modeling, Management and Regulation. (pp. 177-196). New Jersey: John Wiley and Sons.

Abstract

We introduce one-sided cross-validation to nonparametric kernel density estimation. The method is more stable than classical cross-validation and it has a better overall performance comparable to what we see in plug-in methods. One-sided cross-validation is a more direct date driven method than plugin methods with weaker assumptions of smoothness since it does not require a smooth pilot with consistent second derivatives. Our conclusions for one-sided kernel density cross-validation are similar to the conclusions obtained by Hart and Li (1998) when they introduced one-sided cross-validation in the regression context. An extensive simulation study conms that our one-sided cross-validation clearly outperforms the simple cross validation. We conclude with real data applications.

Publication Type: Book Section
Publisher Keywords: bandwidth choice, cross-validation, plug-in, nonparametric estimation 1This
Subjects: H Social Sciences > HB Economic Theory
Departments: Cass Business School > Actuarial Science & Insurance
URI: http://openaccess.city.ac.uk/id/eprint/4635
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