Abstract

This paper focuses on the efficient estimation problem of a more realistic semiparametric SETINAR model of order one with two regimes based on binomial thinning operator. Unlike parametric framework, we do not suppose that the distribution of the innovation process belongs to a parametric family. Instead, the innovation distribution is totally unspecified and is supposed to satisfy only some mild technical assumptions. We, therefore, provide efficient estimators for both parameters of the model, namely a vector of auto-regression parameters and the innovation distribution which is considered as a parameter of infinite-dimension. The performances of these efficient estimators are shown through an intensive simulation study and an application on rotary rig count data in the U.S.A.

摘要

本文重点研究基于二项式细化算子的更现实的一阶二态半参数SETINAR模型的有效估计问题。与参数框架不同，我们不认为创新过程的分布属于参数族。相反，创新分布完全未指定，并且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（即自回归参数向量和被视为无限维参数的创新分布）提供有效的估计器。这些高效估算器的性能通过深入的模拟研究和对美国旋转钻机计数数据的应用来展示