Abstract :We describe the R np package via a series of applications that may be of interest to applied econometricians. The np package implements a variety of nonparametric and semiparametric kernel-based estimators that are popular among econometricians. There are also procedures for nonparametric tests of signicance and consistent model speci-cation tests for parametric mean regression models and parametric quantile regression models, among others. The np package focuses on kernel methods appropriate for the mix of continuous, discrete, and categorical data often found in applied settings. Data-driven methods of bandwidth selection are emphasized throughout, though we caution the user that data-driven bandwidth selection methods can be computationally demanding.
使用半参数想解决的问题是:
假设有7个解释变量,aaa,bbb,ccc,ddd,eee,fff,ggg
1. 确定线性部分的解释变量与非线性部分的解释变量,并找出7个变量中的一个混淆变量
2. 确定半参数变系数分位数回归模型(使用两阶段估计)
3. 对半参数变系数模型中的线性部分进行估计(对于模型中线性部分的系数估计,我们首先将模型中线性部分的变量系数当作非参数形式,利用非参数估计法估计出变量的系数函数,然后对系数函数求均值。)
4. 选取核函数,确定最优带宽
5. 对半参数变系数模型中的非线性部分进行估计(局部多项式线性估计法对变量系数函数做出估计)
最后得出类似于下面图