A uniform weak law of large numbers under π‐mixing with application to nonlinear least squares estimation
A uniform weak law of large numbers under π‐mixing with application to nonlinear least squares estimation
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π混合下大数一致弱定律及其在非线性最小二乘估计中的应用
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发表时间：
1982
期刊：
影响因子：
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通讯作者：
H. Bierens
中科院分区：
文献类型：
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作者：
H. Bierens
在Bierens（1981）中，我们导出了关于有限相依基的随机稳定过程的一个一致弱大数定律。在本文中，我们证明了这个一致弱定律对于更一般的φ-混合基的随机稳定过程是延续的。这种推广将用于放宽非线性最小二乘估计的弱相合性和渐近正态性的条件。
In Bierens (1981) we have derived a uniform weak law of large numbers for stochastically stable processes with respect to a finite-dependent base. In this paper we show that this uniform weak law carries over to stochastically stable processes with respect to a, more general, φ-mixing base. This generalization will be used for relaxing the conditions for weak consistency and asymptotic normality of nonlinear least squares estimators.