Current status linear regression

DOI10.1214/17-AOS1589zbMath1403.62046arXiv1601.00202WikidataQ129617556 ScholiaQ129617556MaRDI QIDQ2413595

Piet Groeneboom, K. Hendrickx

Publication date: 14 September 2018

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1601.00202

zbMATH Keywords

bootstrap methodsemiparametric modelMLElinear regressioncurrent status

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Nonparametric statistical resampling methods (62G09) Estimation in survival analysis and censored data (62N02)

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Cites Work

• Unnamed Item
• Unnamed Item
• A sieve M-theorem for bundled parameters in semiparametric models, with application to the efficient estimation in a linear model for censored data
• Maximum smoothed likelihood estimation and smoothed maximum likelihood estimation in the current status model
• Inconsistency of bootstrap: the Grenander estimator
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Model based bootstrap methods for interval censored data
• Linear regression with interval censored data
• Efficient estimation for the proportional hazards model with interval censoring
• Current status regression.
• Optimal smoothing in single-index models
• Nonparametric Estimation under Shape Constraints
• A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data
• Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
• SOME CONVERGENCE THEORY FOR ITERATIVE ESTIMATION PROCEDURES WITH AN APPLICATION TO SEMIPARAMETRIC ESTIMATION
• Beyond Parametrics in Interdisciplinary Research: Festschrift in Honor of Professor Pranab K. Sen
• Efficiency Bounds for Distribution-Free Estimators of the Binary Choice and the Censored Regression Models
• A Semiparametric Model for Regression Analysis of Interval-Censored Failure Time Data
• Linear Regression with Current Status Data
• A Proportional Hazards Model for Interval-Censored Failure Time Data
• Regression with interval-censored data
• An Efficient Semiparametric Estimator for Binary Response Models
• The Limiting Distribution of the Maximum Rank Correlation Estimator
• Estimation of Semiparametric Models when the Criterion Function Is Not Smooth