Goodness of Fit and Related Inference Processes for Quantile Regression
本文提出了分位数回归的拟合优度过程，类似于最小二乘回归的R2统计量，并构建了检验多个协变量对条件分位数函数联合效应的推断过程，通过实例和蒙特卡洛模拟验证了其有效性。
Abstract We introduce a goodness-of-fit process for quantile regression analogous to the conventional R2 statistic of least squares regression. Several related inference processes designed to test composite hypotheses about the combined effect of several covariates over an entire range of conditional quantile functions are also formulated. The asymptotic behavior of the inference processes is shown to be closely related to earlier p-sample goodness-of-fit theory involving Bessel processes. The approach is illustrated with some hypothetical examples, an application to recent empirical models of international economic growth, and some Monte Carlo evidence.