Bootstrapping the Mean Vector for the Observations in the Domain of Attraction of a Multivariate Stable Law

Autor:	Sohrabi, Maryam, Zarepour, Mahmoud
Rok vydání:	2015
Předmět:	Statistics - Applications Primary 62H10 62G20 Secondary 62G09 62G35
Druh dokumentu:	Working Paper
Popis:	We consider a robust estimation of the mean vector for a sequence of i.i.d. observations in the domain of attraction of a stable law with different indices of stability, $DS(\alpha_1, \ldots, \alpha_p)$, such that $1<\alpha_{i}\leq 2$, $i=1,\ldots,p$. The suggested estimator is asymptotically Gaussian with unknown parameters. We apply an asymptotically valid bootstrap to construct a confidence region for the mean vector. A simulation study is performed to show that the estimation method is efficient for conducting inference about the mean vector for multivariate heavy-tailed distributions. Comment: 13 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1510.01811 Zobrazit plný text záznamu View this record from Arxiv