Asymptotic properties of an estimator in errors-in-variables models in the presence of validation data

Structural errors-in-variables models with dependent spatial observations are studied. The presence of validation data is assumed. An estimator for regression parameters proposed by Lee and Sepanski [1] is studied. Consistency and asymptotic normality of the estimator are established in the case of increasing domain. Infill asymptotic properties are described. Simulation results are also presented.