A Comparison of Hypothesis Testing Methods for the Mean of a Log-Normal Distribution
نویسندگان
چکیده
This paper deals with testing the mean of a log-normal population. We apply a newly developed Computational Approach Test (CAT), which is essentially a parametric bootstrap method. An advantage of the CAT is that it does not require the explicit knowledge of the sampling distribution of the test statistic. The CAT is then compared with three accepted testsCox method, modified Cox method and generalized p-value method with Monte Carlo simulations. Our detailed studies indicate some interesting results including the facts that the size and power of CAT is better than other methods. Using real data, we have illustrated our method.
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