Quantile regression for longitudinal data
Journal of Multivariate Analysis - Special issue on semiparametric and nonparametric mixed models
Computational Statistics & Data Analysis
Editorial for the special issue on quantile regression and semiparametric methods
Computational Statistics & Data Analysis
Transform both sides model: A parametric approach
Computational Statistics & Data Analysis
The jackknife's edge: Inference for censored regression quantiles
Computational Statistics & Data Analysis
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Quantile regression offers a semiparametric approach to modeling data with possible heterogeneity. It is particularly attractive for censored responses, where the conditional mean functions are unidentifiable without parametric assumptions on the distributions. A new algorithm is proposed to estimate the regression quantile process when the response variable is subject to double censoring. The algorithm distributes the probability mass of each censored point to its left or right appropriately, and iterates towards self-consistent solutions. Numerical results on simulated data and an unemployment duration study are given to demonstrate the merits of the proposed method.