论文标题
一致的偏度偏度，偏向数据的偏度
A Consistent Estimator for Skewness of Partial Sums of Dependent Data
论文作者
论文摘要
我们介绍了一种估计方法，用于短和长存储器线性过程的样品平均值的缩放偏度系数。该方法可以扩展到估计较高的矩，例如样品平均值的尺寸系数。同样，还获得了计算所有部分总和的所有渐近力矩的总体结果，特别是对线性过程的某些现有中央限制定理的推导更加容易。引入的偏度估计器提供了一种工具，可以在长期和短内存线性过程中凭经验检查中心极限定理的误差。我们还表明，对于短记忆线性过程，样本平均值的偏度系数以与I.I.D相同的速率收敛到零。案件。
We introduce an estimation method for the scaled skewness coefficient of the sample mean of short and long memory linear processes. This method can be extended to estimate higher moments such as curtosis coefficient of the sample mean. Also a general result on computing all asymptotic moments of partial sums is obtained, allowing in particular a much easier derivation of some existing central limit theorems for linear processes. The introduced skewness estimator provides a tool to empirically examine the error of the central limit theorem for long and short memory linear processes. We also show that, for both short and long memory linear processes, the skewness coefficient of the sample mean converges to zero at the same rate as in the i.i.d. case.
