COMBINING INDEPENDENT INFORMATION IN A MULTIVARIATE CALIBRATION-PROBLEM

The problem of combining independent information from different source s in a multivariate calibration setup is considered. The dimensions of the response vectors from various sources map be unequal. A linear co mbination of the classical estimators based on the individual sources is proposed as an estimator for the unknown explanatory variable. It i s shown that the combined estimator has finite mean provided the sum o f the dimensions of the response vectors exceeds one and has finite me an squared error if it exceeds two. Expressions for asymptotic bias an d mean squared error are given. (C) 1997 Academic Press.