Steffen Betsch, Bruno Ebner
We propose two families of tests for the classical goodness-of-fit problem to univariate normality. The new procedures are based on L2 -distances of the empirical zero-bias transformation to the empirical distribution or the normal distribution function. Weak convergence results are derived under the null hypothesis, under contiguous as well as under fixed alternatives. A comparative finite-sample power study shows the competitiveness to classical procedures.
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