Add to ORKGWe define the appropriate analogue of Student's t-statistic for multivariate data, and prove that it is asymptotically normal for random vectors in the domain of attraction of the normal law. We also prove that Hotelling's T2-statistic has a chi-squared limiting distribution for random vectors in the generalized domain of attraction of the normal law. Our tool in proving these results is the bootstrap. We prove that the bootstrap version of the multivariate t-statistic is asymptotically normal when the parent distribution is in the generalized domain of attraction of the normal law.
AbstractSuppose that Y is distributed as multivariate normal with unknown covariance matrix and that...
In dynamical statistics we are very often confronted with the problem of finding the best analytical...
For the bootstrapped mean, a strong law of large numbers is obtained under the assumption of finiten...
AbstractWe define the appropriate analogue of Student′s t-statistic for multivariate data, and prove...
We define the appropriate analogue of Student′s t-statistic for multivariate data, and prove that it...
We define the appropriate analogue of Student's t-statistic for multivariate data, and prove that it...
Abstract: Problem statement: Hotelling’s T2 statistic has been well documented in the existing liter...
Gine E, Götze F. On standard normal convergence of the multivariate Student t-statistic for symmetri...
It is proved that if the multivariate Student t-statistic based on i.i.d. symmetric random vectors i...
This paper examines the high dimensional asymptotics of the naive Hotelling T2 statistic. Naive Baye...
AbstractThe non-null distributions of Hotelling's T2-statistic and a generalized F-statistic [Biomet...
Many statistics are based on functions of sample moments. Important examples are the sample variance...
AbstractIn this paper we obtain an asymptotic expansion for the distribution of Hotelling'sT2-statis...
AbstractThe asymptotic consistency of the bootstrap approximation of the vector of the marginal gene...
Let X, X-1, X-2,... be i. i. d. R-d-valued random variables. We prove large and moderate deviations ...
AbstractSuppose that Y is distributed as multivariate normal with unknown covariance matrix and that...
In dynamical statistics we are very often confronted with the problem of finding the best analytical...
For the bootstrapped mean, a strong law of large numbers is obtained under the assumption of finiten...
AbstractWe define the appropriate analogue of Student′s t-statistic for multivariate data, and prove...
We define the appropriate analogue of Student′s t-statistic for multivariate data, and prove that it...
We define the appropriate analogue of Student's t-statistic for multivariate data, and prove that it...
Abstract: Problem statement: Hotelling’s T2 statistic has been well documented in the existing liter...
Gine E, Götze F. On standard normal convergence of the multivariate Student t-statistic for symmetri...
It is proved that if the multivariate Student t-statistic based on i.i.d. symmetric random vectors i...
This paper examines the high dimensional asymptotics of the naive Hotelling T2 statistic. Naive Baye...
AbstractThe non-null distributions of Hotelling's T2-statistic and a generalized F-statistic [Biomet...
Many statistics are based on functions of sample moments. Important examples are the sample variance...
AbstractIn this paper we obtain an asymptotic expansion for the distribution of Hotelling'sT2-statis...
AbstractThe asymptotic consistency of the bootstrap approximation of the vector of the marginal gene...
Let X, X-1, X-2,... be i. i. d. R-d-valued random variables. We prove large and moderate deviations ...
AbstractSuppose that Y is distributed as multivariate normal with unknown covariance matrix and that...
In dynamical statistics we are very often confronted with the problem of finding the best analytical...
For the bootstrapped mean, a strong law of large numbers is obtained under the assumption of finiten...