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An accurate test for the equality of covariance matrices from decomposable graphical Gaussian models
(with H. Massam and Y. Wu)
Canadian Journal of Statistics , 42(1), 2014, pp. 61-77
Abstract: This paper derives a saddlepoint based approximation for the cumulative distribution function of the Bartlett-Box M-statistic that tests the equality of covariance matrices for several samples from graphical Gaussian models Markov with respect to a decomposable graph G. The proposed saddlepoint-based method has third-order accuracy (O(n-3/2)). Simulation results show that the proposed method has extremely good coverage properties even when the sample size is small. We apply our method to the well-known Call Centre data set and show that the covariance matrix is not constant through time.
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