Rates of convergence in conditional covariance matrix with nonparametric entries estimation
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Publication:5077524
DOI10.1080/03610926.2019.1602652OpenAlexW2963034918WikidataQ127994600 ScholiaQ127994600MaRDI QIDQ5077524
Maikol Solís, Clément Marteau, Jean-Michel Loubes
Publication date: 18 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1310.8244
Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Statistics (62-XX)
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Cites Work
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- High dimensional covariance matrix estimation using a factor model
- Fisher lecture: Dimension reduction in regression
- Optimal rates of convergence for sparse covariance matrix estimation
- Optimal rates of convergence for covariance matrix estimation
- Covariance regularization by thresholding
- Optimal pointwise adaptive methods in nonparametric estimation
- On consistency and sparsity for sliced inverse regression in high dimensions
- Density estimation by wavelet thresholding
- Asymptotics for kernel estimate of sliced inverse regression
- On the distribution of the largest eigenvalue in principal components analysis
- Nonparametric and semiparametric models.
- Adaptive covariance matrix estimation through block thresholding
- Optimal rates of convergence for estimating Toeplitz covariance matrices
- Nearest neighbor inverse regression
- Regularized estimation of large covariance matrices
- Sparse estimation of large covariance matrices via a nested Lasso penalty
- Estimating the Structural Dimension of Regressions Via Parametric Inverse Regression
- EXACT MEAN INTEGRATED SQUARED ERROR OF HIGHER ORDER KERNEL ESTIMATORS
- Sliced Inverse Regression for Dimension Reduction
- Functional sliced inverse regression analysis
- Asymptotic Statistics
- Efficient estimation of conditional covariance matrices for dimension reduction
- DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES
- Sufficient Dimension Reduction via Inverse Regression
- Convergence of stochastic processes
- Introduction to nonparametric estimation