Approximate maximum likelihood estimation in linear regression

DOI10.1007/BF00773670zbMath0786.62069OpenAlexW1965206075MaRDI QIDQ1260703

Michael A. Magdalinos

Publication date: 25 August 1993

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00773670

zbMATH Keywords

cumulantsasymptotic relative efficiencyapproximate information matrixbiasconfidence intervalleast squares estimatoriteration methodsapproximate maximum likelihoodslope parametersAMLinverse AIMlog likelihood of the disturbancesstandardized cumulantsunobserved errors

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05)

Cites Work

• Semi-Nonparametric Maximum Likelihood Estimation
• Model specification tests. A simultaneous approach
• On asymptotically efficient estimation in semiparametric models
• Monte Carlo evidence on adaptive maximum likelihood estimation of a regression
• Efficient estimation in the errors in variables model
• On adaptive estimation
• Adaptive maximum likelihood estimators of a location parameter
• On adaptive estimation in stationary ARMA processes
• Adaptive estimation of non–linear regression models
• Seminonparametric Estimation of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications
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