Efficient estimation of conditional covariance matrices for dimension reduction

DOI10.1080/03610926.2015.1083109zbMath1368.62136arXiv1110.3238OpenAlexW2963088094MaRDI QIDQ4975151

Maikol Solís, Sébastien Da Veiga, Jean-Michel Loubes

Publication date: 3 August 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1110.3238

zbMATH Keywords

semiparametric estimationTaylor expansionefficient estimationconditional covariance matrix: inverse sliced regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12)

Related Items

Rates of convergence in conditional covariance matrix with nonparametric entries estimation, K-medoids inverse regression

Cites Work

• More on the estimation of distribution densities
• Optimal rates of convergence for covariance matrix estimation
• Covariance regularization by thresholding
• Slicing regression: A link-free regression method
• Asymptotically normal families of distributions and efficient estimation
• Efficient estimation of integral functionals of a density
• Asymptotics for kernel estimate of sliced inverse regression
• Nearest neighbor inverse regression
• Regularized estimation of large covariance matrices
• Estimating the Structural Dimension of Regressions Via Parametric Inverse Regression
• Efficient estimation of sensitivity indices
• Asymptotic Statistics
• Functional sliced inverse regression analysis
• Sufficient Dimension Reduction via Inverse Regression
• Comment