|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, rank, and likelihood ratio tests for the regression parameter estimates
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.
Copyright © SAS Institute, Inc. All Rights Reserved.