Restricted estimation in multivariate measurement error regression model

Authors:
Kanchan Jain;Sukhbir Singh;Suresh Sharma
Affiliations:
-;-;-
Venue:
Journal of Multivariate Analysis
Year:
2011

Citing 4
Cited 1

A note on matrix variate normal distribution

Journal of Multivariate Analysis
Consistent estimation of coefficients in measurement error models with replicated observations

Journal of Multivariate Analysis
Restricted regression estimation in measurement error models

Computational Statistics & Data Analysis
Linear Models and Generalizations: Least Squares and Alternatives

Linear Models and Generalizations: Least Squares and Alternatives

Using stochastic prior information in consistent estimation of regression coefficients in replicated measurement error model

Journal of Multivariate Analysis

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study a multivariate ultrastructural measurement error (MUME) model with more than one response variable. This model is a synthesis of multivariate functional and structural models. Three consistent estimators of regression coefficients, satisfying the exact linear restrictions have been proposed. Their asymptotic distributions are derived under the assumption of a non-normal measurement error and random error components. A simulation study is carried out to investigate the small sample properties of the estimators. The effect of departure from normality of the measurement errors on the estimators is assessed.