Asymptotic normality of Powell%26apos;s kernel estimator

作者：Kato Kengo^*

来源：Annals of the Institute of Statistical Mathematics, 2012, 64(2): 255-273.

DOI：10.1007/s10463-010-0310-9

• Asymptotic normality
• Bandwidth selection
• Censored quantile regression
• Density estimation
• Kernel method
• Quantile regression

We establish asymptotic normality of Powell%26apos;s kernel estimator for the asymptotic covariance matrix of the quantile regression estimator for both i.i.d. and weakly dependent data. As an application, we derive the optimal bandwidth that minimizes the approximate mean squared error of the kernel estimator. We also derive the corresponding results to censored quantile regression.

• 出版日期2012-4