时间：2019年4月17日(周三)上午10:00-11:00
地点：中北校区理科大楼A1514会议室
题目：Model Averaging Estimation for High-dimensional Covariance Matrix with a Network Structure
主讲人：张新雨 中国科学院系统科学研究所
摘要：
In this paper, we develop a model averaging method to estimate the high-dimensional covariance matrix, where the candidate models are constructed by different orders of the polynomial functions. We propose a Mallows-type model averaging criterion and select the weights by minimizing this criterion, which is an unbiased estimator of the expected in-sample squared error plus a constant. Then, we prove the asymptotic optimality of the resulting model average covariance (MAC) estimators. Furthermore, numerical simulations and a case study on Chinese airport network structure data are conducted to demonstrate the usefulness of the proposed approaches.
主讲人简介：
张新雨，中科院系统所/预测中心研究员，主要从事模型平均和模型选择方面的研究工作，在统计学四大期刊和计量经济学顶级期刊Journal of Econometrics发表论文十余篇。曾获优秀青年基金等三项自然科学基金委基金项目资助，目前担任两个SCI期刊编委和Econometrics客座主编。