mvtb.covex: Estimate the covariance explained matrix

In mvtboost: Tree Boosting for Multivariate Outcomes

Description

Estimate the covariance explained matrix

Usage

mvtb.covex(object, Y, X, n.trees = NULL, iter.details = FALSE)

Arguments

object	an object of class mvtb
Y	vector, matrix, or data.frame for outcome variables with no missing values. To easily compare influences across outcomes and for numerical stability, outcome variables should be scaled to have unit variance.
X	vector, matrix, or data.frame of predictors. For best performance, continuous predictors should be scaled to have unit variance. Categorical variables should converted to factors.
n.trees	number of trees to use. Defaults to the minimum number of trees by CV, test, or training error
iter.details	TRUE/FALSE. Return the loss, relative loss, and selected predictors at each iteration as a list

Value

Covariance explained matrix, or a list if iter.details is TRUE.

mvtboost documentation built on May 2, 2019, 2:14 p.m.