Polynomial Histograms for Multivariate Density and Mode Estimation
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]
|Collections||ANU Research Publications|
|Source:||Scandinavian Journal of Statistics|
|01_Jing_Polynomial_Histograms_for_2012.pdf||255.33 kB||Adobe PDF||Request a copy|
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