Estimating coefficients of single-index regression models by minimizing variation

DOI10.1080/00949655.2017.1390574OpenAlexW2766856369MaRDI QIDQ4960549

Dongfang Lou, Zhiyuan Ma

Publication date: 23 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2017.1390574

zbMATH Keywords

iterative marginal optimizationminimum variation estimationsingle-index regression model

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Rank-based inference for the single-index model
• A note on iterative marginal optimization: a simple algorithm for maximum rank correlation estimation
• Semiparametric analysis of discrete response. Asymptotic properties of the maximum score estimator
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Slicing regression: A link-free regression method
• Maximum score estimation of the stochastic utility model of choice
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Direct estimation of the index coefficient in a single-index model
• Optimal smoothing in single-index models
• Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
• ASYMPTOTIC DISTRIBUTIONS FOR TWO ESTIMATORS OF THE SINGLE-INDEX MODEL
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• Mathematical Statistics
• An Adaptive Estimation of Dimension Reduction Space
• Semiparametric Estimation of Index Coefficients
• An Efficient Semiparametric Estimator for Binary Response Models
• The Limiting Distribution of the Maximum Rank Correlation Estimator

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