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Covariance-Guided Mixture Probabilistic Principal Component Analysis (C-MPPCA)

To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful. However, a single two-dimensional ...
JSTOR DailyLíon na míonna: 6

HYPOTHESIS TESTING FOR THE COVARIANCE MATRIX IN HIGH-DIMENSIONAL TRANSPOSABLE DATA WITH KRONECKER PRODUCT DEPENDENCE STRUCTURE

The matrix-variate normal distribution is a popular model for high-dimensional transposable data because it decomposes the dependence structure of the random matrix into the Kronecker product of two ...