Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data-Reference-Cited by-同舟云学术

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Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data

Published:2011-12 Issue:12 Volume:121 Page:2925-2953
ISSN:0304-4149
Container-title:Stochastic Processes and their Applications
language:en
Short-container-title:Stochastic Processes and their Applications

Author:

Csörgő Miklós,Martsynyuk Yuliya V.

Publisher

Elsevier BV

Subject

Applied Mathematics,Modelling and Simulation,Statistics and Probability

Reference14 articles.

1. Convergence of Probability Measures;Billingsley,1968

2. Consistency for least squares regression estimators with infinite variance data;Cline;J. Statist. Plann. Inference,1989

3. Donsker’s theorem for self-normalized partial sums processes;Csörgő;Ann. Probab.,2003

4. M-estimation for linear regression with infinite variance;Davis;Probab. Math. Statist.,1997

5. When is the Student t-statistic asymptotically standard normal?;Giné;Ann. Probab.,1997

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Two-Dimensional Anisotropic Random Walks: Fixed Versus Random Column Configurations for Transport Phenomena;Journal of Statistical Physics;2018-04-20

2. Precise Asymptotics in Strong Limit Theorems for Self-normalized Sums of Multidimensionally Indexed Random Variables;Asymptotic Laws and Methods in Stochastics;2015

3. Invariance principles for a multivariate Student process in the generalized domain of attraction of the multivariate normal law;Statistics & Probability Letters;2012-12

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