Add to ORKGAbstract: 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
Combining forecasts have been proven as one of the most successful methods to improve predictive per...
We introduce various methods that combine forecasts using constrained optimization with penalty. A n...
Abstract: We analyze macroeconomic data using univariate and multivariate forecast combining techniq...
We use the Pitman-closeness criterion to evaluate the performance of multivariate forecasting method...
We specify the Pitman-closeness criterion for the evaluation of multivariate forecasts in three cate...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
A general method for determining Pitman Nearness is given In the case of univariate estimators. This...
We give an equivalent definition of Pitman’s closeness criterion, in terms of medians of the differe...
The linear combination of forecasts is a procedure that has improved the forecasting accuracy for d...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
This paper proposes a framework for the analysis of the theoretical properties of forecast combinati...
The linear combination of forecasts is a procedure that has improved the forecasting accuracy for di...
AbstractIn a multiparameter estimation problem, for first-order efficient estimators, second-order P...
This paper brings together two important but hitherto largely unrelated areas of the forecasting lit...
Combining forecasts have been proven as one of the most successful methods to improve predictive per...
We introduce various methods that combine forecasts using constrained optimization with penalty. A n...
Abstract: We analyze macroeconomic data using univariate and multivariate forecast combining techniq...
We use the Pitman-closeness criterion to evaluate the performance of multivariate forecasting method...
We specify the Pitman-closeness criterion for the evaluation of multivariate forecasts in three cate...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
We consider Pitman-closeness to evaluate the performance of forecasting methods. Optimal weights for...
A general method for determining Pitman Nearness is given In the case of univariate estimators. This...
We give an equivalent definition of Pitman’s closeness criterion, in terms of medians of the differe...
The linear combination of forecasts is a procedure that has improved the forecasting accuracy for d...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
This paper proposes a framework for the analysis of the theoretical properties of forecast combinati...
The linear combination of forecasts is a procedure that has improved the forecasting accuracy for di...
AbstractIn a multiparameter estimation problem, for first-order efficient estimators, second-order P...
This paper brings together two important but hitherto largely unrelated areas of the forecasting lit...
Combining forecasts have been proven as one of the most successful methods to improve predictive per...
We introduce various methods that combine forecasts using constrained optimization with penalty. A n...
Abstract: We analyze macroeconomic data using univariate and multivariate forecast combining techniq...