Sufficient dimension reduction with simultaneous estimation of effective dimensions for time-to-event data

DOI10.5705/ss.202017.0550zbMath1453.62458OpenAlexW2954307359WikidataQ129416320 ScholiaQ129416320MaRDI QIDQ5134477

Ming-Yueh Huang, Kwun Chuen Gary Chan

Publication date: 16 November 2020

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/b59572195edc45f0d7788a92f552cf241636b319

zbMATH Keywords

counting processcentral subspacehigher-order kernelstructural dimensiondata-adaptive band-width

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (2)

A Review on Sliced Inverse Regression, Sufficient Dimension Reduction, and Applications ⋮ Ultrahigh-dimensional sufficient dimension reduction for censored data with measurement error in covariates

Uses Software

• GrassmannOptim

Cites Work

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• Efficient estimation in sufficient dimension reduction
• A constructive approach to the estimation of dimension reduction directions
• Sliced Regression for Dimension Reduction
• Sufficient dimension reduction based on an ensemble of minimum average variance estimators
• Optimal bandwidth selection in nonparametric regression function estimation
• On Kullback-Leibler loss and density estimation
• Dimension reduction for censored regression data
• Uniform strong representation of the conditional Kaplan-Meier process
• Kernel dimension reduction in regression
• Sufficient Dimension Reduction for Censored Regressions
• EXACT MEAN INTEGRATED SQUARED ERROR OF HIGHER ORDER KERNEL ESTIMATORS
• Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression
• Simulation and the Asymptotics of Optimization Estimators
• Dimension reduction for non-elliptically distributed predictors: second-order methods
• On Directional Regression for Dimension Reduction
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• Sliced Inverse Regression for Dimension Reduction
• The Geometry of Algorithms with Orthogonality Constraints
• A Semiparametric Approach to Dimension Reduction
• Gradient-Based Kernel Dimension Reduction for Regression
• Dimension Reduction and Semiparametric Estimation of Survival Models
• Dimension Reduction in Regressions Through Cumulative Slicing Estimation
• Inverse Regression Estimation for Censored Data
• A validated information criterion to determine the structural dimension in dimension reduction models
• Function minimization by conjugate gradients
• On Sliced Inverse Regression With High-Dimensional Covariates

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