Large p Small n Data: Inference for the Mean
Thursday 20th January 2011
Secchi, P.; Stamm, A.; Vantini, S.
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.