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- SAS/STAT Procedures A-Z
The QUANTREG Procedure
- models the effects of covariates on the conditional quantiles of a response variable by means of quantile regression
- 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 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
- obtain separate analyses on observations in groups
- perform weighted estimation
- creates an output data set containing predicted values, residuals, estimated standard errors, and other statistics
- creates an output data set containing the parameter estimates for all quantiles
- uses ODS to create a SAS data set corresponding to any table
- supports ODS Graphics
For further details see the SAS/STAT User's Guide:
The QUANTREG Procedure
( PDF | HTML )
Examples
- Comparison of Algorithms
- Quantile Regression for Econometric Growth Data
- Quantile Regression Analysis of Birth-Weight Data
- Nonparametric Quantile Regression for Ozone Levels
- Quantile Polynomial Regression for Salary Data
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