摘要：When a model of main research interest shares partial parameters with several other models, it is of bene_t to incorporate the information contained in these other models to improve the estimation and prediction for the main model of interest. Various methods are possible to make use of the additional models as well as the additional observations related to these models. We propose an optimal strategy of doing so in terms of prediction. We develop the model averaging methodology and obtain the optimal weights. We also establish theory to support the method and show its desirable properties both when the main model is correct and when it is incorrect. Numerical experiments including simulation studies and data analysis are conducted to demonstrate the superior performance of our methods.
简介：张新雨，中国科学院数学与系统科学研究院/中国科学院预测科学研究中心研究员，智源青年科学家；曾在德州农工大学做博士后研究，担任期刊《Journal of Systems Science and Complexity》领域主编、期刊《Statistical Analysis and Data Mining》AE、以及期刊《系统科学与数学》、《应用概率统计》的编委，是双法学会数据科学分会副理事长和国际统计学会当选会员。