Composite Forecasting: An Integrated Approach and Optimality Reconsidered
指出组合预测的拉格朗日乘子解在回归表示下通常不是最优的，并给出了基于N个预测的最优线性预测器，同时通过实证表明该解在估计中可能接近最优。
This article shows when the theoretical Lagrange multiplier solution for combining forecasts has a regression representation. This solution is not optimal in general because it imposes a restriction on an otherwise more general linear form. The optimal linear predictor based on N forecasts is presented. This predictor is or is not a regression function depending on whether the latter function is linear. I also show that the Lagrange multiplier solution may often be nearly optimal. Hence, when estimating a composite forecast, the restriction imposed by this solution may prove useful. This observation is supported in an empirical example.