regstat: An Exact Test for a Change in Covariance (Dependence) Structure
An exact finite-sample test for whether two groups share a covariance matrix, the
omnibus form of the differential-network question. Under the Gaussian null the
likelihood-ratio statistic has a distribution given by the real Jacobi ensemble that is
free of the unknown common covariance, so a single Monte-Carlo calibration at the identity
serves every covariance with no estimate of the nuisance covariance; this is the property
that survives the dimension barrier, where estimating the covariance is hardest. The
max-type high-dimensional test of Cai, Liu and Xia (2013)
<doi:10.1080/01621459.2012.758041> is provided for comparison. A pure-C back-end does the
numerics and also backs the 'Python' package 'regstat'.
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