Bias of ml and reml estimators in regression models with arma errors

DOI10.1080/00949658908811169zbMath0718.62194OpenAlexW2054125389MaRDI QIDQ5750227

Clyde A. McGilchrist

Publication date: 1989

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949658908811169

zbMATH Keywords

biasARMA modelserror varianceautoregressive moving average structureaverage biasesREML techniques

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Monte Carlo methods (65C05)

Related Items (5)

Flexible and efficient estimating equations for variogram estimation ⋮ On a class of change-point models in covariance structures for growth curves and repeated measurements ⋮ Biases of the restricted maximum likelihood estimators for ARMA processes with polynomial time trend ⋮ A note on the difference between two likelihood based methods in growth curves ⋮ Model selection with misspecified spatial covariance structure

Cites Work

• Monte Carlo Comparison of ANOVA, MIVQUE, REML, and ML Estimators of Variance Components
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• Recovery of inter-block information when block sizes are unequal

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