predict.cv.mcen: Makes predictions from the model with the smallest...

In mcen: Multivariate Cluster Elastic Net

Makes predictions from the model with the smallest cross-validation error.

Description

Makes predictions from the model with the smallest cross-validation error.

Usage

## S3 method for class 'cv.mcen'
predict(object, newx, ...)

Arguments

object	The cv.mcen object.
newx	The X matrix of predictors.
...	Additional parameters to be sent to predict.

Value

Returns the predicted values from the model with the smallest cross-validation error.

Author(s)

Ben Sherwood <[e-mail]>, Brad Price <[e-mail]>

Examples

x <- matrix(rnorm(400),ncol=4)
beta <- beta <- matrix(c(1,1,0,0,0,0,-1,-1,0,0,-1,-1,1,1,0,0),ncol=4)
y <- x%*%beta + rnorm(400) 
mcen_fit <- cv.mcen(x,y,ky=2,gamma_y=3)
new_x <- matrix(rnorm(12),ncol=4)
mcen_preds <- predict(mcen_fit, new_x)

mcen documentation built on April 1, 2023, 12:11 a.m.