example.multiclass: Simulated data with multi-categorical outcome

In xtune: Regularized Regression with Feature-Specific Penalties Integrating External Information

Simulated data with multi-categorical outcome

Description

The simulated data contains 600 observations, 800 predictors, 10 covariates, and an multiclass outcome with three categories. The external information Z contains five indicator prior covariates.

Usage

data(example.multiclass)

Format

The example.multiclass object is a list containing three elements:

• X: A simulated 600 by 800 matrix

• Y: Categorical outcome with three levels

• U: Covariates matrix with 600 by 10 dimension, will be forced in the model

• Z: A 800 by 5 matrix with indicator entries.

Examples

data(example.multiclass)
X <- example.multiclass$X
Y <- example.multiclass$Y
U <- example.multiclass$U
Z <- example.multiclass$Z
fit <- xtune(X = X,Y = Y, U = U, Z = Z, family = "multiclass", c = 0.5)
fit$penalty.vector

xtune documentation built on July 9, 2023, 5:22 p.m.