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 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.

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.

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.

Objectives:Group-randomized designs are well suited for studies of professional development because they can accommodate programs that are delivered to intact groups (e.g., schools), the collaborative nature of professional development, and extant teacher/school assignments. Though group designs...