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Joint convergence of high dimensional sample autocovariance matrices
澳门新葡8455最新网站:2019年12月06日 16:08 点击数:

报告人:Arup Bose

报告地点:澳门新葡8455最新网站415会议室

报告澳门新葡8455最新网站:2019年12月08日星期日10:30-11:30

邀请人:郑术蓉

报告摘要:

We consider a class of high dimensional time series models. The sample autocovariances carry crucial statistical information on the model.

We study the joint convergence of the symmetrized version of these matrices in two senses: the algebraic sense (tracial convergence) and the existence of the limit spectral distribution of any symmetric polynomial of these matrices.

The limit description involve non-commutative variables which are free.

主讲人概况:

Arup Bose is a Professor at the Indian Statistical Institute. He has been holding the J.C.Bose Fellowship since 2009. He is an elected Fellow of the Institute of Mathematical Statistics (USA), and all three national sciences academies of India. He is also an elected member of the International Statistical Institute. He has been an Invited speaker at the ICM 2010 and a Distinguished Lecturer at the 2nd APRM. He is a winner of the Shanti Swarup Bhatnagar Award in Mathematical Sciences, the National Award in Statistics as well as the Young Researcher Award of IISA (USA). His current research interests are in Large dimensional random matrices, Free probability, High Dimensional Time series and Moral hazard problems in economics.

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