Some aspects of multivariate calibration with incomplete designs
There has been some debate whether inverse or classical calibration methods are superior when there are multivariate predictors and some of them are missing. In this paper, we compare these two methods in the case where the design is not completely known. We develop some general results in the multivariate case and carry out extensive simulations in a univariate model with partly known regressors and several error distributions. These simulations reveal that the methods perform differently, depending on the specifics of the model. Neither method, however, turns out to be consistently superior to the other.