On Asymptotic Optimality of Likelihood Ratio Tests for Multivariate Normal Distributions
Hsieh, H. K.
Ann. Statist., Tome 7 (1979) no. 1, p. 592-598 / Harvested from Project Euclid
In multivariate analysis under normality assumptions, many likelihood ratio criteria $(\lambda^{(n)})$ are distributed as $k\prod^m_{i=1} Z^a_{li}(1 - Z_{li})^{b_i}\prod^{m'}_{j=1} Z^{c_j}_{2j}$ for some constants, $k, m, m', a_i, b_i,$ and $c_j$ when their associated null hypotheses are true, where $Z_{ij}$ are independently distributed beta variates. Let $T^{(n)} = -n^{-1} \ln \lambda^{(n)}$. This paper shows that a sequence $\{T^{(n)}\}$ of this kind is asymptotically optimal in the sense of exact slopes. Explicit forms of the exact slopes are obtained.
Publié le : 1979-05-14
Classification:  Multivariate hypothesis testing problem,  likelihood ratio criterion,  exact slope,  asymptotically optimal test,  62F20,  62H15,  62F05
@article{1176344680,
     author = {Hsieh, H. K.},
     title = {On Asymptotic Optimality of Likelihood Ratio Tests for Multivariate Normal Distributions},
     journal = {Ann. Statist.},
     volume = {7},
     number = {1},
     year = {1979},
     pages = { 592-598},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176344680}
}
Hsieh, H. K. On Asymptotic Optimality of Likelihood Ratio Tests for Multivariate Normal Distributions. Ann. Statist., Tome 7 (1979) no. 1, pp.  592-598. http://gdmltest.u-ga.fr/item/1176344680/