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The LIL Convergence for Stationary Linear Random Field
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作者 He Shuyuan Department of Probability and Statistics Peking University Beijing, 100871 China 《Acta Mathematica Sinica,English Series》 SCIE CSCD 1996年第4期385-397,共13页
Let Y={Y_n;n∈N^2} be a stationary linear random field generated by a two- dimensional martingale difference. Where N^2 denotes the two dimensional integer lattice. The main purpose of this paper is to obtain the LIL ... Let Y={Y_n;n∈N^2} be a stationary linear random field generated by a two- dimensional martingale difference. Where N^2 denotes the two dimensional integer lattice. The main purpose of this paper is to obtain the LIL convergence for the partial-sums of Y. 展开更多
关键词 stationary linear random field 1/4 Martingale difference LIL convergency.
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Limsup Results and LIL for Partial Sum Processes of a Gaussian Random Field 被引量:1
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作者 Yong-Kab CHOI Mikls CSRG 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2008年第9期1497-1506,共10页
Let {&#958;<SUB> j </SUB>; j &#8712; &#8484;<SUB>+</SUB><SUP> d </SUP>be a centered stationary Gaussian random field, where &#8484;<SUB>+</SUB><SUP>... Let {&#958;<SUB> j </SUB>; j &#8712; &#8484;<SUB>+</SUB><SUP> d </SUP>be a centered stationary Gaussian random field, where &#8484;<SUB>+</SUB><SUP> d </SUP>is the d-dimensional lattice of all points in d-dimensional Euclidean space &#8477;<SUP>d</SUP>, having nonnegative integer coordinates. For each j = (j <SUB>1 </SUB>, ..., jd) in &#8484;<SUB>+</SUB><SUP> d </SUP>, we denote |j| = j <SUB>1 </SUB>... j <SUB>d </SUB>and for m, n &#8712; &#8484;<SUB>+</SUB><SUP> d </SUP>, define S(m, n] = &#931;<SUB> m【j&#8804;n </SUB>&#950;<SUB> j </SUB>, &#963;<SUP>2</SUP>(|n&#8722;m|) = ES <SUP>2 </SUP>(m, n], S <SUB>n </SUB>= S(0, n] and S <SUB>0 </SUB>= 0. Assume that &#963;(|n|) can be extended to a continuous function &#963;(t) of t 】 0, which is nondecreasing and regularly varying with exponent &#945; at b &#8805; 0 for some 0 【 &#945; 【 1. Under some additional conditions, we study limsup results for increments of partial sum processes and prove as well the law of the iterated logarithm for such partial sum processes. 展开更多
关键词 stationary Gaussian random field regularly varying function large deviation probability law of the iterated logarithm
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