De-Biased Sparse PCA: Inference for Eigenstructure of Large Covariance Matrices
From MaRDI portal
Publication:5001646
DOI10.1109/TIT.2021.3059765zbMath1473.62204OpenAlexW3131424090MaRDI QIDQ5001646
Jana Janková, Sara van de Geer
Publication date: 22 July 2021
Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1109/tit.2021.3059765
Factor analysis and principal components; correspondence analysis (62H25) Parametric tolerance and confidence regions (62F25) Ridge regression; shrinkage estimators (Lasso) (62J07)
Related Items (5)
The asymptotic distribution of the MLE in high-dimensional logistic models: arbitrary covariance ⋮ Covariance structure estimation with Laplace approximation ⋮ Statistical Inference for High-Dimensional Generalized Linear Models With Binary Outcomes ⋮ Inference for low-rank models ⋮ Scale calibration for high-dimensional robust regression
This page was built for publication: De-Biased Sparse PCA: Inference for Eigenstructure of Large Covariance Matrices