Abstract
This paper proposes a normalizing transformation which removes bias, skewness and kurtosis, simultaneously. Its convergence rate to the standard normal distribution is o(n-1). The transformation is polynomial and monotone. We consider a class of asymptotic U-statistics, which includes most of interesting statistics.
| Original language | English |
|---|---|
| Pages (from-to) | 47-74 |
| Number of pages | 28 |
| Journal | Journal of Statistical Planning and Inference |
| Volume | 83 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 1 2000 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics
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Fujioka, Y., & Maesono, Y. (2000). Higher order normalizing transformations of asymptotic U-statistics for removing bias, skewness and kurtosis. Journal of Statistical Planning and Inference, 83(1), 47-74. https://doi.org/10.1016/s0378-3758(99)00087-7