Monte Carlo Evaluation of Resampling-Based Hypothesis Tests
نویسنده
چکیده
Monte Carlo estimation of the power of tests that require resampling can be very com-putationally intensive. It is possible to reduce the size of the inner resampling loop as long as the resulting estimator of power can be corrected for bias. A simple linear extrapolation method is shown to perform well in correcting for bias and thus reduces computation time in Monte Carlo power studies.
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تاریخ انتشار 1998