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The effect of temporal aggregation on the estimation accuracy of time series models

机译:时间聚合对时间序列模型估计精度的影响

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摘要

In time series analysis, Autoregressive Moving Average (ARMA) models play a central role. Because of the importance of parameter estimation in ARMA modeling and since it is based on aggregate time series so often, we analyze the effect of temporal aggregation on estimation accuracy. We derive the relationships between the aggregate and the basic parameters and compute the actual values of the former from those of the latter in order to measure and compare their estimation accuracy. We run a simulation experiment that shows that aggregation seriously worsens estimation accuracy and that the impact increases with the order of aggregation.
机译:在时间序列分析中,自回归移动平均线(ARMA)模型起着核心作用。由于参数估计在ARMA建模中非常重要,并且由于它经常基于集合时间序列,因此我们分析了时间集合对估计精度的影响。我们推导了聚合和基本参数之间的关系,并从后者的基础值计算前者的实际值,以测量和比较其估计精度。我们运行了一个仿真实验,结果表明聚合严重降低了估计的准确性,并且影响随着聚合顺序的增加而增加。

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