Large p Small n Data: Inference for the Mean

Code:
06/2011
Title:
Large p Small n Data: Inference for the Mean
Date:
Thursday 20th January 2011
Author(s):
Secchi, P.; Stamm, A.; Vantini, S.
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Abstract:
We provide a generalization of Hotelling’s Theorem that enables inference (i)for the mean vector of a multivariate normal population and (ii) for the comparison of the mean vectors of two multivariate normal populations, when the number p of components is larger than the number n of sample units and the (common) covariance matrix is unknown. We find suitable test statistics and their p-asymptotic distributions that allow the inferential analysis of large p small n data.