predict.glmaag: Prediction for glmaag

In glmaag: Adaptive LASSO and Network Regularized Generalized Linear Models

Description

Prediction using glmaag model

Usage

## S3 method for class 'glmaag'
predict(object, x, lam1, lam2, type = "link",
  cutp = 0.5, ...)

Arguments

object	fitted glmaag object
x	The new dataset to be predicted, do training prediction if x is missing
lam1	lambda1 sequence for prediction, must be within the fitted model
lam2	lambda2 sequence for prediction, must be within the fitted model
type	type of prediction (can be "link", "reponse"), ignored for Gaussian model. "link" is the linear predicted score, "response" is the predicted probability for logistic model and relative risk for Cox model
cutp	the cut off value for binary outcome, default to be 0.5
...	...

Value

predicted values

Examples

data(sampledata)
data(L0)
y <- sampledata$Y_Gau
x <- sampledata[, -(1:3)]
mod <- glmaag(y, x, L0)
pp <- predict(mod)

glmaag documentation built on May 10, 2019, 9:04 a.m.