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STRONG APPROXIMATION FOR MOVING AVERAGE PROCESSES UNDER DEPENDENCE ASSUMPTIONS
作者姓名:林正炎  李德柜
作者单位:Department of Mathematics, Zhejiang University, Hangzhou 310027, China
基金项目:Supported by NSFC (10571159) and SRFDP (20060335032)
摘    要:Let {Xt,t ≥ 1} be a moving average process defined by Xt = ∑^∞ k=0 αkξt-k, where {αk,k ≥ 0} is a sequence of real numbers and {ξt,-∞ 〈 t 〈 ∞} is a doubly infinite sequence of strictly stationary dependent random variables. Under the conditions of {αk, k ≥ 0} which entail that {Xt, t ≥ 1} is either a long memory process or a linear process, the strong approximation of {Xt, t ≥ 1} to a Gaussian process is studied. Finally, the results are applied to obtain the strong approximation of a long memory process to a fractional Brownian motion and the laws of the iterated logarithm for moving average processes.

关 键 词:线性过程  近似值  对数  数学
收稿时间:2006-01-25

Strong Approximation for Moving Average Processes Under Dependence Assumptions
Lin Zhengyan,Li Degui,.STRONG APPROXIMATION FOR MOVING AVERAGE PROCESSES UNDER DEPENDENCE ASSUMPTIONS[J].Acta Mathematica Scientia,2008,28(1):217-224.
Authors:Lin Zhengyan  Li Degui  
Institution:aDepartment of Mathematics, Zhejiang University, Hangzhou 310027, China
Abstract:Strong approximation, long memory process, linear process, fractional Brownian motion, the law of the iterated logarithm
Keywords:Strong approximation  long memory process  linear process  fractional Brownian motion  the law of the iterated logarithm
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