On estimation of a heteroscedastic measurement error model under heavy-tailed distributions

DOI10.1016/j.csda.2011.08.011zbMath1239.62067OpenAlexW2091253439MaRDI QIDQ425409

Jin-Guan Lin, Chun-Zheng Cao, Xiao-Xin Zhu

Publication date: 8 June 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.08.011

zbMATH Keywords

EM algorithmmaximum likelihoodequation errorscale mixtures of normal distribution

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Estimation in survival analysis and censored data (62N02)

Related Items (8)

Robust replicated heteroscedastic measurement error model using heavy-tailed distribution ⋮ Bayesian inference in a heteroscedastic replicated measurement error model using heavy-tailed distributions ⋮ Heteroscedastic replicated measurement error models under asymmetric heavy-tailed distributions ⋮ Improved estimation in a general multivariate elliptical model ⋮ A heteroscedastic measurement error model based on skew and heavy-tailed distributions with known error variances ⋮ Influence diagnostics for Grubbs's model with asymmetric heavy-tailed distributions ⋮ Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error ⋮ Modelling financial time series based on heavy-tailed market microstructure models with scale mixtures of normal distributions

Cites Work

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• A heteroscedastic structural errors-in-variables model with equation error
• On estimation and local influence analysis for measurement errors models under heavy-tailed distributions
• On estimation and influence diagnostics for the Grubbs' model under heavy-tailed distributions
• Assessment of diagnostic procedures in symmetrical nonlinear regression models
• Estimating the dimension of a model
• Robust inference in an heteroscedastic measurement error model
• Measurement Error in Nonlinear Models

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