A Nonparametric Hypothesis Test via the Bootstrap Resampling
نویسنده
چکیده
This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test.
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تاریخ انتشار 2001