Estimating spatial quantile regression with functional coefficients: A robust semiparametric framework

作者：Lu Zudi^*; Tang Qingguo; Cheng Longsheng

来源：Bernoulli, 2014, 20(1): 164-189.

DOI：10.3150/12-BEJ480

• asymptotic distributions
• functional (varying) coefficient spatial regression
• local M-estimators
• quantile regression
• robust framework
• soil data analysis
• spatial data

This paper considers an estimation of semiparametric functional (varying)-coefficient quantile regression with spatial data. A general robust framework is developed that treats quantile regression for spatial data in a natural semiparametric way. The local M-estimators of the unknown functional-coefficient functions are proposed by using local linear approximation, and their asymptotic distributions are then established under weak spatial mixing conditions allowing the data processes to be either stationary or nonstationary with spatial trends. Application to a soil data set is demonstrated with interesting findings that go beyond traditional analysis.

• 出版日期2014-2
• 单位南京理工大学