Positive-definite regularized estimation for high-dimensional covariance on scalar regression

Covariance is an important measure of marginal dependence among variables. However, heterogeneity in subject covariances and regression models for high-dimensional covariance matrices is not well studied. Compared to regression analysis for conditional means, modeling high-dimensional covariances is...

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Veröffentlicht in:	Biometrics Jg. 81; H. 1
Hauptverfasser:	He, Jie, Qiu, Yumou, Zhou, Xiao-Hua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England 07.01.2025
Schlagworte:	Algorithms Biometry - methods Brain - physiology Computer Simulation Data Interpretation, Statistical Humans Models, Statistical Regression Analysis fMRI data high dimensionality ADMM algorithm regularization conditional average covariance matrix positive-definiteness constraint
ISSN:	0006-341X, 1541-0420, 1541-0420
Online-Zugang:	Volltext
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