A common procedure when combining two multivariate unbiased estimates (or forecasts) is the covariance adjustment technique (CAT). Here the optimal combination weights depend on the covariance structure of the estimators. In practical applications, however, this covariance structure is hardly...

We specify the Pitman-closeness criterion for the evaluation of multivariate forecasts in three categories. This is done closely to the definition of covariance adjustment techniques analysed in other articles. We also apply the Pitman-closeness techniques to an example dealing with German...

We use the Pitman-closeness criterion to evaluate the performance of multivariate forecasting methods and we also calculate optimal matrices of weights for the linear combination of multivariate forecasts. These weights are identical with the optimal weights under the matrix-MSE criterion.

When a forecaster predicts the future value of a certain random variable it is very likely that he will not only forecast that certain variable but he will also forecast other variables from the same field. In the literature on the combination of several individual forecasts univariate...