s.RLM

Numeric vector or matrix / data frame of features i.e. independent variables

Numeric vector of outcome, i.e. dependent variable

Numeric vector or matrix / data frame of testing set features
Columns must correspond to columns in <code>x</code>

x.test

Numeric vector of testing set outcome

y.test

Additional parameters to be passed to <code>MASS::rlm</code>

Convenience alias for <code>s.LM(robust = T)</code>. Uses <code>MASS::rlm</code>

Advanced Machine Learning and Visualization made efficient and accessible. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression, Survival Analysis), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and dynamic graphs.

s.RLM: Robust linear model

Description

Usage

Arguments