Abstract

The efficient estimation problem of a semi-parametric first-order periodic integer-valued autoregressive (PINAR(1)) model is considered. The unspecified distribution of the innovation process of this model is suposed to satisfy only some mild technical assumptions. We therefore provide efficient estimates for both parameters of the model, namely a periodic autoregressive parameter and a periodic probability law of the innovation non-negative integer values process which is seen as an infinite dimensional parameter. The performances of these efficient estimations are shown through intensive simulations studies and an application on real data set.

中文翻译：

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(PINAR(1)) 模型中的有效估计：半参数情况

摘要

考虑了半参数一阶周期整数值自回归 ( PINAR (1)) 模型的有效估计问题。该模型的创新过程的未指定分布应该仅满足一些温和的技术假设。因此，我们为模型的两个参数提供了有效估计，即周期性自回归参数和创新非负整数值过程的周期性概率定律，这被视为无限维参数。通过深入的模拟研究和对真实数据集的应用，展示了这些有效估计的性能。