Combining independent information in a multivariate calibration problem

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

[发布日期] 1997-05-01

[关键词] bias;classical estimator;Cholesky decomposition;mean squared error