Maximal Moment Inequality for Partial Sums of Strong Mixing Sequences and Application  

作　　者：Shah Chao YANG 

机构地区：[1]Department of Mathematics, Guangxi Normal University, Guilin 541004, P. R. China

出　　处：《Acta Mathematica Sinica,English Series》2007年第6期1013-1024,共12页数学学报（英文版）

基　　金：the Natural Science Foundation of China(10161004);the Natural Science Foundation of Guangxi(04047033)

摘　　要：Some maximal moment inequalities for partial sums of the strong mixing random variable sequence are established. These inequalities use moment sums as up-boundary and improve the corre- sponding ones obtained by Shao （1996）. To show the application of the inequalities, we apply them to discuss the asymptotic normality of the weight function estimate for the fixed design regression model.Some maximal moment inequalities for partial sums of the strong mixing random variable sequence are established. These inequalities use moment sums as up-boundary and improve the corre- sponding ones obtained by Shao （1996）. To show the application of the inequalities, we apply them to discuss the asymptotic normality of the weight function estimate for the fixed design regression model.

关 键 词：strong mixing maximal moment inequality fixed design regression model weight functionestimate asymptotic normality 

分 类 号：O17[理学—数学]