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Suppose we observe data of the form $Y_i = D_i (S_i + \varepsilon_i) \in \mathbb{R}^p$ or $Y_i = D_i S_i + \varepsilon_i \in \mathbb{R}^p$, $i=1,\ldots,n$, where $D_i \in \mathbb{R}^{p\times p}$ are known diagonal matrices, $\varepsilon_i$ are noise, and we wish to perform principal component analysis (PCA) on the unobserved signals $S_i \in \mathbb{R}^p$.
Distribution of eigenvalues for some sets of random matrices
V. A. Marchenko and L. A. Pastur · 1967
Earlier work this paper cites.
Linear bayesian methods
J. Hartigan · 1969
Earlier work this paper cites.
Fundamentals of Statistical Signal Processing: Estimation Theory , volume 3
S. M. Kay · 1993
Earlier work this paper cites.
Chapter 3 - two-dimensional averaging techniques
J. Frank · 1996
Earlier work this paper cites.
Analysis of incomplete multivariate data
J. L. Schafer · 1997
Earlier work this paper cites.
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Z.-D. Bai and J. W. Silverstein · 1998
Earlier work this paper cites.
On the distribution of the largest eigenvalue in principal components analysis
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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