Non-parametric maximum likelihood estimation of censored regression models

DOI10.1016/0304-4076(86)90011-4zbMath0604.62034OpenAlexW1988896174MaRDI QIDQ1083147

B. George

Publication date: 1986

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(86)90011-4

zbMATH Keywords

consistencyasymptotic normalityconsistent estimatorrelative efficiencyMonte Carlo experimentscensored linear regression modelmajorizing regression vectornon-parametric likelihood functionalPowell's least absolute deviations

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items (10)

Pairwise difference estimators of censored and truncated regression models ⋮ A comparison of semi-parametric and partially adaptive estimators of the censored regression model with possibly skewed and leptokurtic error distributions ⋮ Recent contributions to censored regression models ⋮ Estimation of Type 3 Tobit models using symmetric trimming and pairwise comparisons ⋮ Partially Adaptive Estimation of the Censored Regression Model ⋮ Randomly censored partially linear single-index models ⋮ Nonparametric regression with filtered data ⋮ Censored multiple regression by the method of average derivatives ⋮ Semiparametric estimation of employment duration models ⋮ Quantile regression under random censoring.

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