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首页> 外文期刊>Journal of Time Series Analysis >ROBUST FITTING OF INARCH MODELS
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ROBUST FITTING OF INARCH MODELS

机译:稳健的Inarch模型

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摘要

We discuss robust M-estimation of INARCH models for count time series. These models assume the observation at each point in time to follow a Poisson distribution conditionally on the past, with the conditional mean being a linear function of previous observations. This simple linear structure allows us to transfer M-estimators for autoregressive models to this situation, with some simplifications being possible because the conditional variance given the past equals the conditional mean. We investigate the performance of the resulting generalized M-estimators using simulations. The usefulness of the proposed methods is illustrated by real data examples.
机译:我们讨论了计数时间序列的INARCH模型的鲁棒M估计。这些模型假定每个时间点的观测值都遵循过去的条件泊松分布,条件均值是先前观测值的线性函数。这种简单的线性结构使我们可以将自回归模型的M估计器转移到这种情况,因为过去给出的条件方差等于条件均值,因此可以进行一些简化。我们使用模拟研究所得的广义M估计量的性能。实际数据示例说明了所提出方法的有效性。

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