A Bootstrap's Reliability Measure on Tests of Hypotheses

Bootstrapping has gained popularity in different tests of hypotheses as an alternative in using asymptotic distribution if one is not sure of the distribution of the test statistic under a null hypothesis. This method, in general, has two variants – the parametric and the nonparametric approaches. However, issues on reliability of this method always arise in many applications. This paper addresses the issue on reliability by establishing a reliability measure in terms of quantiles with respect to asymptotic distribution, when this is approximately correct. The test of hypotheses used is Ftest. The simulated results show that using nonparametric bootstrapping in F-test gives better reliability than parametric bootstrapping with relatively higher degrees of freedom.

• Al Jefferson J. Pabelic
• Dennis A. Tarepe

• F-test
• nonparametric bootstrapping
• parametric bootstrapping
• reliability measure
• tests of hypotheses.

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