Prediction using many samples with models containing partially shared parameters
作者:
时间:2020-10-19
阅读量:349次
  • 演讲人: 张新雨(中科院数学与系统科学研究院/预测中心研究员)
  • 时间:2020年11月04日 星期三 14:00(北京时间)
  • 地点:腾讯会议 会议 ID:630 326 858
  • 主办单位:浙江大学数据科学研究中心


 摘要:When a model of main research interest shares partial parameters with several other models, it is of benefit 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,中科院数学与系统科学研究院/预测中心研究员。在中科院系统所获得博士学位学位,曾在TAMU和PSU做博士后研究。主要从事计量经济学和统计学的理论和应用研究工作,具体研究方向包括模型平均、模型选择和组合预测等。担任期刊《JSSC》领域主编、期刊《SADM》、《系统科学与数学》、《应用概率统计》的编委。先后主持国家自然科学基金委优秀和杰出青年研究基金项目,曾获得中国管理学青年奖和中科院优秀博士学位论文等奖励。

 

主持人:张荣茂教授  浙江大学数学科学学院