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講座題目：Sublinear expectation linear regression

報告人：林路教授，山東大學kaiyun開云官方網(wǎng)站

主持人：    鄭海濤教授
講座時間：  2013年11月8日上午10:30am-11:30am

講座地點：  九里校區(qū)電氣館3215

內容簡介：Nonlinear expectation, including sublinear expectation as its special case, is a new and original framework of probability theory and has potential applications in some scientific fields, especially in finance risk measure and econometrics. Under the nonlinear expectation framework, however, the related statistical models and statistical inferences have not yet been well established. The goal of this paper is to construct the sublinear expectation regression and investigate its statistical inference. First, a sublinear expectation linear regression is defined and its identifiability is given. Then, based on the representation theorem of sublinear expectation and the newly defined model, several parameter estimations and model predictions are suggested, the asymptotic normality of estimations and the mini-max property of predictions are obtained. Furthermore, new methods are developed to realize variable selection for high-dimensional model. Finally, simulation studies and a real financial example are carried out to illustrate the new models and methodologies.
All notions and methodologies developed are essentially different from classical ones and can be thought of as a foundation for general nonlinear expectation statistics.

報告人簡介：林路教授，山東大學金融研究院副院長。學術領域覆蓋Nonparametric Statistics; Robust Statistics; Statistical Depth; Quasi-Likelihood and Empirical Likelihood; Financial Statistics and Statistics in F-BSDE; High dimensional Models，現(xiàn)已發(fā)表60多篇高水平論文，其中多數(shù)為SCI論文。主持或完成3項國家自然科學基金和多項省部級項目。曾多次訪問北美和歐洲高水平大學和研究機構。 

主辦：研究生院
承辦：kaiyun開云官方網(wǎng)站