data.train: Training data

In FADA: Variable Selection for Supervised Classification in High Dimension

Description

Simulated training dataset. The x component is a matrix of explanatory variables, with 30 rows and 250 columns. Each row is simulated according to a multinormal distribution which mean depends on a group membership given by the y component. The variance matrix is the same within each group.

Usage

data(data.train)

Format

A list with 2 components. x is a 30x250 matrix of simulated explanatory variables. y is a 30x1 grouping variable (coded 1 and 2).

Examples

data(data.train)
dim(data.train$x) # 30 250
data.train$y # 2 levels
hist(cor(data.train$x[data.train$y==1,])) # high dependence 
hist(cor(data.train$x[data.train$y==2,]))

Example output

Loading required package: MASS
Loading required package: elasticnet
Loading required package: lars
Loaded lars 1.2

[1]  30 250
 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

FADA documentation built on Dec. 10, 2019, 5:07 p.m.