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Nonparametric testing of closeness between two unknown distribution functions
Authors:Qi Li
Institution:  a Department of Economics, University of Guelph, Guelph, Ontario, Canada
Abstract:Based on the kernel integrated square difference and applying a central limit theorem for degenerate V-statistic proposed by Hall (1984), this paper proposes a consistent nonparametric test of closeness between two unknown density functions under quite mild conditions. We only require the unknown density functions to be bounded and continuous. Monte Carlo simulations show that the proposed tests perform well for moderate sample sizes.
Keywords:Nonparametric Test  Unknown Densities  Kernel Estimation  Asymptotic Normality  Smoothing Parameter
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