The QUANTREG Procedure


The main features of the QUANTREG procedure are as follows:

  • offers simplex, interior point, and smoothing algorithms for estimation

  • provides sparsity, rank, and resampling methods for confidence intervals

  • provides asymptotic and bootstrap methods for covariance and correlation matrices of the estimated parameters

  • provides the Wald, likelihood ratio, and rank tests for the regression parameter estimates and the Wald test for heteroscedasticity

  • provides outlier and leverage-point diagnostics

  • enables parallel computing when multiple processors are available

  • provides row-wise or column-wise output data sets with multiple quantiles

  • provides regression quantile spline fits

  • produces fit plots, diagnostic plots, and quantile process plots by using ODS Graphics

The next section provides notation and a formal definition for quantile regression.