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Maximal Moment Inequality for Partial Sums of Strong Mixing Sequences and Application 被引量:13
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作者 Shah Chao YANG 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2007年第6期1013-1024,共12页
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 ... 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. 展开更多
关键词 strong mixing maximal moment inequality fixed design regression model weight functionestimate asymptotic normality
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