Abstract
In this paper two approaches to multivariate linear calibration in linear models are compared. One of these approaches is based on knowledge of the distribution of the variable to be predicted. The other one uses only information about the measurement instrument. The methods are compared with respect to risk function and their functional relationship is analysed. When concerns risk functions we concentrate on asymptotic results.