Rank regression for current-status data: Asymptotic normality

DOI10.1016/S0167-7152(98)00267-3zbMath0923.62073OpenAlexW2003975608WikidataQ127330436 ScholiaQ127330436MaRDI QIDQ1292781

Jason Abrevaya

Publication date: 31 October 1999

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-7152(98)00267-3

zbMATH Keywords

interval censoring\(U\)-statisticsrank estimators

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (4)

Nonparametric regression with current status data ⋮ Extremal ranks of matrix expression of \(A - BXC\) with respect to Hermitian matrix ⋮ Combining Multiple Markers for Classification Using ROC ⋮ Leapfrog estimation of a fixed-effects model with unknown transformation of the dependent variable

Cites Work

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• Asymptotic efficiency in semi-parametric models with censoring
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Rank regression for current status data
• An Empirical Distribution Function for Sampling with Incomplete Information
• Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model
• Efficiency Bounds for Distribution-Free Estimators of the Binary Choice and the Censored Regression Models
• The Limiting Distribution of the Maximum Rank Correlation Estimator

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