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  "Title": "Principal Component Analysis in High-Dimensional Data",
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  "Description": "In high-dimensional settings: Estimate the number of\ndistant spikes based on the Generalized Spiked Population (GSP)\nmodel. Estimate the population eigenvalues, angles between the\nsample and population eigenvectors, correlations between the\nsample and population PC scores, and the asymptotic shrinkage\nfactors. Adjust the shrinkage bias in the predicted PC scores.\nDey, R. and Lee, S. (2019) <doi:10.1016/j.jmva.2019.02.007>.",
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