Nonparametric testing of closeness between two unknown distribution functions |
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Authors: | Qi Li |
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Affiliation: | a Department of Economics, University of Guelph, Guelph, Ontario, Canada |
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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. |
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Keywords: | Nonparametric Test Unknown Densities Kernel Estimation Asymptotic Normality Smoothing Parameter |
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