Multivariate density estimation using dimension reducing information and tail flattening transformations

Tine Buch-Kromann, Montserrat Guillen, Oliver Linton and Jens Perch Nielsen

Insurance: Mathematics and Economics, 2011, vol. 48, issue 1, 99-110

Abstract: We propose a nonparametric multiplicative bias corrected transformation estimator designed for heavy tailed data. The multiplicative correction is based on prior knowledge and has a dimension reducing effect at the same time as the original dimension of the estimation problem is retained. Adding a tail flattening transformation improves the estimation significantly-particularly in the tail-and provides significant graphical advantages by allowing the density estimation to be visualized in a simple way. The combined method is demonstrated on a fire insurance data set and in a data-driven simulation study.

Keywords: Bias; reduction; Kernel; Multiplicative; correction (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:48:y:2011:i:1:p:99-110

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