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Polynomial Histograms for Multivariate Density and Mode Estimation

Jing, Junmei; Koch, Inge; Naito, Kanta

Description

We consider the problem of efficiently estimating multivariate densities and their modes for moderate dimensions and an abundance of data. We propose polynomial histograms to solve this estimation problem. We present first- and second-order polynomial histogram estimators for a general d-dimensional setting. Our theoretical results include pointwise bias and variance of these estimators, their asymptotic mean integrated square error (AMISE), and optimal binwidth. The asymptotic performance of...[Show more]

CollectionsANU Research Publications
Date published: 2012
Type: Journal article
URI: http://hdl.handle.net/1885/61156
Source: Scandinavian Journal of Statistics
DOI: 10.1111/j.1467-9469.2011.00764.x

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