Consistent estimation of regression parameters under replicated ultrastructural model with non-normal errors

Abstract

This article discusses the construction and efficiency properties of consistent estimators of regression parameters under replicated ultrastructural model with not necessarily normally distributed measurement errors. The variances of measurement errors associated with the study and explanatory variables are estimated from the replicated sample observations and are used for the consistent estimation of regression parameters. The asymptotic efficiency properties of the estimators are derived and analysed. The finite sample performance of the estimators is empirically studied through a Monte Carlo simulation.

Keywords:

• measurement errors
• direct regression
• reverse regression
• replicated data
• ultrastructural model
• non-normal distribution