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Efficient inference about the tail weight in multivariate Student t distributions

par Ley, Christophe ;Neven, Anouk
Référence Journal of statistical planning and inference, 167, page (123-134)
Publication Publié, 2015-12

Article révisé par les pairs

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Résumé :

We propose a new testing procedure about the tail weight parameter of multivariate Student t distributions by having recourse to the Le Cam methodology. Our test is asymptotically as efficient as the classical likelihood ratio test, but outperforms the latter by its flexibility and simplicity: indeed, our approach allows to estimate the location and scatter nuisance parameters by any root-. n consistent estimators, hereby avoiding numerically complex maximum likelihood estimation. The finite-sample properties of our test are analyzed in a Monte Carlo simulation study, and we apply our method on a financial data set. We conclude the paper by indicating how to use this framework for efficient point estimation.