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Han Yu

Northwest Missouri State University



76 – Density Estimation

Kernel-based Kullback-Leibler Divergence on Nonparametric Density Alternatives

Sponsor: Section on Nonparametric Statistics
Keywords: Goodness-of-Fit, density estimator, Kullback-Leibler, kernel smoothing

Han Yu

Northwest Missouri State University

A kernel-based Kullback-Leibler divergence is proposed. The proposed Kullback-Leibler divergence are used for tests on nonparametric density alternatives that are developed to be asymptotically distribution-free. The procedure can be viewed as a nonparametric extension of the traditional parametric likelihood ratio tests. Simulations of the proposed tests are provided for the small sample size performance.

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