AIC and BIC rules for the number of significant principal components in multivariate extremes are developed and shown to be weakly consistent under a spiked covariance model.
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Estimation of the number of principal components in high-dimensional multivariate extremes
AIC and BIC rules for the number of significant principal components in multivariate extremes are developed and shown to be weakly consistent under a spiked covariance model.