学术活动

Exact Moderate and Large Deviations for Sums of Dependent Random Variables

2018-06-13 17:00

报告人: 桑海林 【密西西比大学】

报告人单位:

时间: 2018-06-13 17:00-18:00

地点: 卫津路校区bat365正版唯一官网6号楼111教室

开始时间: 2018-06-13 17:00-18:00

报告人简介:

年:

日月:

 

报告人简介

密西西比大学副教授

报告内容介绍

       Large and moderate deviation probabilities play an important role in many applied areas, such as insurance and risk analysis. In this talk we first study the exact moderate and large deviation asymptotics in non-logarithmic form for linear processes with independent innovations with p th (p>2) moment and regular varying right tails. The linear processes we analyzed are general and therefore they include the long memory case. We give an asymptotic representation for probability of the tail of the normalized sums and specify the zones in which it can be approximated either by a standard normal distribution or by the marginal distribution of the innovation process. We also extend the results to linear random fields. The results are then applied to regression estimates, moving averages, fractionally integrated processes, linear processes with regularly varying exponents, functions of linear processes and Davis-Gut law of the iterated logarithm.
      We also study the moderate deviation under the Cramer condition for sums of random fields by applying the conjugate method. The results are applicable to the partial sums of linear random fields with short or long memory and to nonparametric regression with random field errors. (This talk is based on joint work of three papers with Aleksandr Beknazaryan, Magda Peligrad, Wei Biao Wu, Yimin Xiao and Yunda Zhong.)


Contact us

Add:bat·365(中国)唯一官方网站 -Mobile Lgoin Center,

        No. 135, Ya Guan Road, Jinnan District, Tianjin, PRC 

Tel:022-60787827   Mail:math@tju.edu.cn