predict.apple: Model prediction based on a fitted apple/cv.apple object.

In apple: Approximate Path for Penalized Likelihood Estimators

Description

Similar to other predict methods, this function returns predictions from a fitted "apple" or "cv.apple" object.

Usage

## S3 method for class 'apple'
predict(object, X, which = 1:length(object$lambda), 
type = c("link", "response", "class"),...)

Arguments

object	fitted "apple" or "cv.apple" model object.
X	matrix of values at which predictions are to be made.
which	indices of the penalty parameter lambda at which predictions are required. by default, all indices are returned.
type	type of prediction: "link" returns the linear predictors; "response" gives the fitted values; "class" returns the binomial outcome with the highest probability.
...	see matplot.

Value

The object returned depends on type.

Author(s)

Yi Yu and Yang Feng

References

Yi Yu and Yang Feng, APPLE: Approximate Path for Penalized Likelihood Estimator, manuscript.

See Also

apple, cv.apple and plot.apple

Examples

p=10
n=200
d=5
coefs=c(3,1.5,0,0,2)
intercept=0
beta=rep(0,p)
beta[1:d]=coefs
set.seed(2)
X=matrix(rnorm(p*n), nrow=n)
mu=1/(1+exp(-X %*% beta-intercept))
y=rbinom(n,1,mu)
	

fit.apple=apple(X, y, family="binomial")


set.seed(3)
testX=matrix(rnorm(p*n), nrow=n)

predict(fit.apple,testX,type="link")
predict(fit.apple,testX,type="response")
predict(fit.apple,testX,type="class")


fit=cv.apple(X, y, family="binomial", alpha=0)
predict(fit.apple,testX,type="link", which = fit$cv.loc)
predict(fit.apple,testX,type="response", which = fit$cv.loc)
predict(fit.apple,testX,type="class", which = fit$cv.loc)

apple documentation built on May 2, 2019, 3:23 a.m.