We propose an alternative ('dual regression') to the quantile regression process for the global estimation of … conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the … quantile regression process while largely avoiding the need for 'rearrangement' to repair the intersecting conditional quantile …

We propose dual regression as an alternative to the quantile regression process for the global estimation of … conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the … quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile …

OLS estimator in a rank-rank regression. We show that the probability limits of these estimators may be too large or too …

random variable Y is median uncorrelated with a k-dimensional random vector X if and only if the slope from an LAD regression …

This paper is concerned with testing rationality restrictions using quantile regression methods. Specifically, we … unobservable. To analyze the economic restriction, we employ quantile regression methods because they allow us to utilize the … Regression …

This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is … component functions in additive quantile regression models. -- Bahadur representation ; Censored data ; Kernel smoothing … ; Quantile regression ; Semiparametric models …