Robust replicated heteroscedastic measurement error model using heavy-tailed distribution
Chunzheng Cao, Mengqian Chen, Yuqian Ren, Yue Xu · Communications in Statistics - Simulation and Computation · 2017
Heteroscedastic measurement error models are widely used in epidemiological, analytical chemistry, and other research areas. In this article, we propose a heteroscedastic measurement error model for replicated data under scale mixtures of normal distributions with/without equation error, which covers unpair and/or unequal replication cases. We obtain iterative formulas of maximum likelihood estimations via EM algorithm, and provide closed forms of asymptotic variances of the estimators. Simulation studies and a real data application are reported to investigate the effective and robust performances of the model and estimates.