A Novel Nonparametric Density Estimator
Data(s) |
12/11/2006
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Resumo |
We present a novel nonparametric density estimator and a new data-driven bandwidth selection method with excellent properties. The approach is in- spired by the principles of the generalized cross entropy method. The pro- posed density estimation procedure has numerous advantages over the tra- ditional kernel density estimator methods. Firstly, for the first time in the nonparametric literature, the proposed estimator allows for a genuine incor- poration of prior information in the density estimation procedure. Secondly, the approach provides the first data-driven bandwidth selection method that is guaranteed to provide a unique bandwidth for any data. Lastly, simulation examples suggest the proposed approach outperforms the current state of the art in nonparametric density estimation in terms of accuracy and reliability. |
Identificador |
http://espace.library.uq.edu.au/view/UQ:12535/Nonparametric_estimation.pdf |
Palavras-Chave | #nonparametric density estimation #statistics #230000 Mathematical Sciences |
Tipo |
Seminar Paper |