Second-order least squares estimation of censored regression models

DOI10.1016/j.jspi.2008.04.016zbMath1149.62011OpenAlexW2066283415MaRDI QIDQ958763

Liqun Wang, Taraneh Abarin

Publication date: 8 December 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2008.04.016

zbMATH Keywords

consistencyasymptotic normalityTobit modelM-estimatorcensored regression modelasymmetric errorsweighted (nonlinear) least squares

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Parametric inference under constraints (62F30) Monte Carlo methods (65C05)

Related Items (4)

Robust second-order least-squares estimator for regression models ⋮ New optimal design criteria for regression models with asymmetric errors ⋮ Second-order least-squares estimation for regression models with autocorrelated errors ⋮ Finite mixture modeling of censored regression models

Cites Work

• Unnamed Item
• Unnamed Item
• Estimation of Relationships for Limited Dependent Variables
• Second-order nonlinear least squares estimation
• Least absolute deviations estimation for the censored regression model
• Estimation of censored linear errors-in-variables models
• Adaptively truncated maximum likelihood regression with asymmetric errors.
• Estimation of nonlinear models with Berkson measurement errors
• Symmetrically Trimmed Least Squares Estimation for Tobit Models
• Regression Analysis when the Dependent Variable Is Truncated Normal
• Robust estimation for linear regression with asymmetric errors
• Asymptotic Properties of Non-Linear Least Squares Estimators

This page was built for publication: Second-order least squares estimation of censored regression models