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Maximal Moment Inequality for Partial Sums of Strong Mixing Sequences and Application 被引量:13

Maximal Moment Inequality for Partial Sums of Strong Mixing Sequences and Application
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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.
出处 《Acta Mathematica Sinica,English Series》 SCIE CSCD 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)
关键词 strong mixing maximal moment inequality fixed design regression model weight functionestimate asymptotic normality strong mixing, maximal moment inequality, fixed design regression model, weight functionestimate, asymptotic normality
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