Least squares estimation in the monotone single index model

DOI10.3150/18-BEJ1090zbMath1433.62108arXiv1610.06026MaRDI QIDQ2325372

Fadoua Balabdaoui, Hanna K. Jankowski, Cécile Durot

Publication date: 25 September 2019

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1610.06026

zbMATH Keywords

monotonemaximum likelihoodleast squaressingle-index modelsemi-parametricshape-constraints

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) General nonlinear regression (62J02)

Related Items (15)

Convergence guarantee for the sparse monotone single index model ⋮ On the population least‐squares criterion in the monotone single index model ⋮ Semiparametric Efficiency in Convexity Constrained Single-Index Model ⋮ Distributional (Single) Index Models ⋮ Isotonic recalibration under a low signal-to-noise ratio ⋮ Behaviour of the monotone single index model under repeated measurements ⋮ Empirical Bayes Mean Estimation With Nonparametric Errors Via Order Statistic Regression on Replicated Data ⋮ Empirical likelihood inference for monotone index model ⋮ Shape constraints in economics and operations research ⋮ Limit theory in monotone function estimation ⋮ Nonparametric shape-restricted regression ⋮ Score estimation of monotone partially linear index model ⋮ Sample selection models with monotone control functions ⋮ Least squares estimation in the monotone single index model ⋮ Profile Least Squares Estimators in the Monotone Single Index Model

Uses Software

• dobson
• scar

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Regression analysis under link violation
• Direct estimation of the index coefficient in a single-index model
• Current status regression.
• Weak convergence and empirical processes. With applications to statistics
• Least squares estimation in the monotone single index model
• Optimal smoothing in single-index models
• Current status linear regression
• Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach
• Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
• Elliptically Symmetric Distributions: A Review and Bibliography
• On the optimality of the random hyperplane rounding technique for MAX CUT
• High-dimensional estimation with geometric constraints: Table 1.
• Quasi-Likelihood Regression with Multiple Indices and Smooth Link and Variance Functions
• Structured Signal Recovery From Non-Linear and Heavy-Tailed Measurements
• Generalized Additive and Index Models with Shape Constraints
• Identifiability of single-index models and additive-index models
• The Number of Linearly Inducible Orderings of Points in d-Space

This page was built for publication: Least squares estimation in the monotone single index model