Density estimates of low bias

Christopher Withers and Saralees Nadarajah ()

Metrika: International Journal for Theoretical and Applied Statistics, 2013, vol. 76, issue 3, 357-379

Abstract: Two methods are given for adapting a kernel density estimate to obtain an estimate of a density function with bias O(h p ) for any given p, where h=h(n) is the bandwidth and n is the sample size. The first method is standard. The second method is new and involves use of Bell polynomials. The second method is shown to yield smaller biases and smaller mean squared errors than classical kernel density estimates and those due to Jones et al. (Biometrika 82:327–338, 1995 ). Copyright Springer-Verlag 2013

Keywords: Bias reduction; Density estimates; Kernel (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00184-012-0392-x

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