Box–Cox transformations and heavy-tailed distributions
| Autor: | Giovanni Vanroelen, Jef L. Teugels |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Statistics and Probability
Stylized fact General Mathematics 010102 general mathematics Estimator Power transform 01 natural sciences 010104 statistics & probability Transformation (function) Statistics Econometrics Statistical analysis 0101 mathematics Statistics Probability and Uncertainty Mathematics |
| Zdroj: | Journal of Applied Probability. 41:213-227 |
| ISSN: | 1475-6072 0021-9002 |
| DOI: | 10.1017/s0021900200112306 |
| Popis: | It is a stylized fact that estimators in extreme-value theory suffer from serious bias. Moreover, graphical representations of extremal data often show erratic behaviour. In the statistical literature it is advised to use a Box–Cox transformation in order to make data more suitable for statistical analysis. We provide some of the theoretical background to see the effect of such transformations and to investigate under what circumstances they might be helpful. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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