无穷维自回归过程的中偏差原理(英文)  

Moderate Deviation Principle for Infinite-dimensional Autoregressive Processes

作　　者：沈思[1] 苗雨[2] 

机构地区：[1]中央民族大学理学院,北京100081 [2]河南师范大学数学与信息科学学院,河南新乡453007

出　　处：《应用数学》2009年第4期791-798,共8页Mathematica Applicata

基　　金：Supported by the Key Science Project for Young Teachers of Minzu University of China

摘　　要：本文考虑无穷维自回归过程经验协方差函数的中偏差原理,仅对自回归过程的随机扰动项做了高斯可积性的假设,这个条件比[4]中的对数Sobolev不等式要弱很多.主要利用了m-相依随机变量的中偏差结果和Ellis-Gartner定理,推广了[6]的结果.A moderate deviation principle of the empirical covariance for infinite-dimensional autoregressive processes is established. The main assumption on the autoregressive process is the Gaussian integrability condition for the noise, which is weaker than the assumption of Logarithmic Sobolev Inequality in [-4]. By the moderate deviation principles of m- dependent random variables and Ellis- Gartner Theorem,we extend the results in [6].

关 键 词：中偏差 自回归过程 

分 类 号：O211.6[理学—概率论与数理统计]