论文标题
拆分 - 结合单纯形的组合和预测者的选择
Split-then-Combine simplex combination and selection of forecasters
论文作者
论文摘要
本文考虑了分裂的结合方法（STC）方法（Arroyo和de Juan，2014年），以将单纯性空间内的预测组合在一起，即正重的样品空间，总计高达一个。事实证明，单纯形中心给出的简单统计量与固定重量的平均预测有利。此外，我们还开发了一种联合隔离（CAS）方法来摆脱冗余预报员。我们采用这两种方法来将几个经济变量的预测提前组合和次级组合组合。当样本量小于预测数量时，此方法特别有用，这种情况是其他方法（例如最小二乘（LS）或主成分分析（PCA））不适用的情况。
This paper considers the Split-Then-Combine (STC) approach (Arroyo and de Juan, 2014) to combine forecasts inside the simplex space, the sample space of positive weights adding up to one. As it turns out, the simplicial statistic given by the center of the simplex compares favorably against the fixed-weight, average forecast. Besides, we also develop a Combine-After-Selection (CAS) method to get rid of redundant forecasters. We apply these two approaches to make out-of-sample one-step ahead combinations and subcombinations of forecasts for several economic variables. This methodology is particularly useful when the sample size is smaller than the number of forecasts, a case where other methods (e.g., Least Squares (LS) or Principal Component Analysis (PCA)) are not applicable.
