Two-Step Likelihood Estimation Procedure for Varying-Coefficient Models
Two-Step Likelihood Estimation Procedure for Varying-Coefficient Models
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DOI：
10.1006/jmva.2001.2013
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发表时间：
2002-07
影响因子：
1.6
通讯作者：
Z. Cai
中科院分区：
文献类型：
--
作者：
Z. Cai
变系数模型的优点之一是允许系数作为其他变量的光滑函数变化，并且可以通过简单的局部拟似然方法容易地估计模型。这导致简单的一步估计过程。我们表明，这样的一步方法不能是最佳的，当一些系数函数具有不同程度的光滑。这个缺点可以通过使用两步估计方法来减弱。证明了两步方法的渐近正态性和均方误差，并证明了两步估计不仅具有最优收敛速度，而且与已知其他系数函数的理想情况具有相同的最优性.数值研究进行说明的两步方法。
One of the advantages for the varying-coefficient model is to allow the coefficients to vary as smooth functions of other variables and the model can be estimated easily through a simple local quasi-likelihood method. This leads to a simple one-step estimation procedure. We show that such a one-step method cannot be optimal when some coefficient functions possess different degrees of smoothness. This drawback can be attenuated by using a two-step estimation approach. The asymptotic normality and mean-squared errors of the two-step method are obtained and it is also shown that the two-step estimation not only achieves the optimal convergent rate but also shares the same optimality as the ideal case where the other coefficient functions were known. A numerical study is carried out to illustrate the two-step method.