grpQreg: Grouped Quantile Regression

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

This is analagous to the grpOLS function, except quantile regression replaces ordinary least squares.

Usage

grpQreg(X, Y, idx, ranks = NULL, q = 0.5, tol = 1e-05, maxiter = 100)

Arguments

X	a model matrix (must be numeric, not categorical)
Y	the outcome variable (must be numeric, not categorical)
idx	group id labels
ranks	an indicator for each group whether the covariates of said group are active.
q	the quantile of interest. defaults to 0.50.

Value

an sdr object

References

Liu, Y., Chiaromonte, F. and Li, B. (2017) Structured Ordinary Least Squares: A Sufficient Dimension Reduction approach for regressions with partitioned predictors and heterogeneous units. Biom, 73: 529-539. doi:10.1111/biom.12579

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.