grpOLS: Grouped Ordinary Least Squares

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

Description

This is similar to the gOLS function in the sSDR package, but slightly simplified in usage and better handling of ill-conditioned matrices. Note that the covariates in this method must be numeric, and not grouped dummy variable representing a factor.

Usage

grpOLS(X, Y, idx, ranks = NULL, 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.

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.