Limiting properties of the least squares estimator of a continuous threshold autoregressive model
Limiting properties of the least squares estimator of a continuous threshold autoregressive model
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DOI：
10.1093/biomet/85.2.413
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发表时间：
1998-06-01
期刊：
影响因子：
2.7
通讯作者：
Tsay, RS
中科院分区：
文献类型：
--
作者：
Chan, KS;Tsay, RS
连续门限自回归模型是门限自回归模型的一个子类，要求分段线性自回归函数处处连续。与不连续情形相比，证明了在适当的正则性条件下，包括阈值参数在内的参数的条件最小二乘估计是n阶相合的，且渐近正态分布.该理论通过模拟研究来说明，并应用于美国季度失业率。
The continuous threshold autoregressive model is a sub-class of the threshold autoregressive model subject to the requirement that the piece-wise linear autoregressive function be continuous everywhere. In contrast with the discontinuous case, it is shown that, under suitable regularity conditions, the conditional least squares estimator of the parameters including the threshold parameter is root-n consistent and asymptotically normally distributed. The theory is illustrated by a simulation study and is applied to the quarterly U.S. unemployment rates.