@inproceedings{0ad86392bb854262ac7ad5b2d354779f,

title = "The likelihood ratio test for equality of mean vectors with compound symmetric covariance matrices",

abstract = "The author derives the likelihood ratio test statistic for the equality of mean vectors when the covariance matrices are assumed to have a compound symmetric structure. Its exact distribution is then expressed in terms of a product of independent Beta random variables and it is shown that for some particular cases it is possible to obtain very manageable finite form expressions for the probability density and cumulative distribution functions for this distribution. For the other cases, given the intractability of the expressions for the exact distribution, very sharp near-exact distributions are developed. Numerical studies show the extreme good performance of these near-exact distributions.",

keywords = "Beta distributions, Exact distribution, Likelihood ratio statistic, Near-exact distributions",

author = "Coelho, {Carlos A.}",

note = "sem pdf. FCT–Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia (Portuguese Foundation for Science and Technology), project UID/MAT/00297/2013, through Centro de Matem{\'a}tica e Aplica{\c c}{\~o}es (CMA/FCT-UNL); 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference date: 03-07-2017 Through 06-07-2017",

year = "2017",

month = jan,

day = "1",

doi = "10.1007/978-3-319-62404-4_2",

language = "English",

isbn = "978-3-319-62403-7",

volume = "10408 LNCS",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "20--32",

booktitle = "Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017",

address = "Germany",

}