168 citations · 513 across the 11 of their papers we have counts for
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Notes on asymptotics of sample eigenstructure for spiked covariance models with non-Gaussian data
Iain M. Johnstone, Jeha Yang
These expository notes serve as a reference for an accompanying post Morales-Jimenez et al. [2018]. In the spiked covariance model, we develop results on asymptotic normality of sa…
Asymptotics of eigenstructure of sample correlation matrices for high-dimensional spiked models
David Morales-Jimenez, Iain M. Johnstone, Matthew R. McKay +1
Sample correlation matrices are employed ubiquitously in statistics. However, quite surprisingly, little is known about their asymptotic spectral properties for high-dimensional da…
Spiked covariances and principal components analysis in high-dimensional random effects models
Zhou Fan, Iain M. Johnstone, Yi Sun
We study principal components analyses in multivariate random and mixed effects linear models, assuming a spherical-plus-spikes structure for the covariance matrix of each random e…
Fast and Accurate Binary Response Mixed Model Analysis via Expectation Propagation
P. Hall, I. M. Johnstone, J. T. Ormerod +2
Expectation propagation is a general prescription for approximation of integrals in statistical inference problems. Its literature is mainly concerned with Bayesian inference scena…