Bias-Corrected Maximum Likelihood Estimators in Nonlinear Heteroscedastic Models

DOI10.1080/03610920802571138zbMath1170.62045OpenAlexW2076318918MaRDI QIDQ3396352

Audrey H. M. A. Cysneiros, Francisco José A. Cysneiros, Gauss M. Cordeiro

Publication date: 18 September 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802571138

zbMATH Keywords

nonlinear modelinformation matrixmaximum likelihoodcumulantbias correctionheteroscedastic modelmethod of scoring

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) General nonlinear regression (62J02)

Related Items

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: estimation and case influence diagnostics

Uses Software

• R
• Ox

Cites Work

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• Improved point and interval estimation for a beta regression model
• On bootstrap and analytical bias corrections
• Corrected maximum-likelihood estimation in a class of symmetric nonlinear regression models
• A third-order bias corrected estimate in generalized linear models
• Bartlett corrections and bias correction for two heteroscedastic regression models
• Editorial: Special Issue on Statistical Inference on Time Series Stochastic and Deterministic Dynamics
• Bias in nonlinear regression
• Heteroscedastic Nonlinear Regression
• Bias corrected estimates in multivariate student t regression models
• Bias reduction of maximum likelihood estimates
• Corrected estimates for Studenttregression models with unknown degrees of freedom