| Autor: |
Betsch, Steffen, Ebner, Bruno |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
TEST, Volume 29, Issue 1, pages 105-138, (2020) |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1007/s11749-019-00630-0 |
| Popis: |
We propose two families of tests for the classical goodness-of-fit problem to univariate normality. The new procedures are based on $L^2$-distances of the empirical zero-bias transformation to the normal distribution or the empirical distribution of the data, respectively. Weak convergence results are derived under the null hypothesis, under fixed alternatives as well as under contiguous alternatives. Empirical critical values are provided and a comparative finite-sample power study shows the competitiveness to classical procedures. |
| Databáze: |
arXiv |
| Externí odkaz: |
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