predict.StaPLRcoef {mvs}

Make predictions from a "StaPLRcoef" object.

Description

Predict using a "StaPLRcoef" object. A "StaPLRcoef" object can be considerably smaller than a full "StaPLR" object for large data sets.

Usage

## S3 method for class 'StaPLRcoef'
predict(object, newx, view, newcf = NULL, predtype = "response", ...)

Arguments

object

Extracted StaPLR coefficients as a "StaPLRcoef" object.

newx

Matrix of new values for x at which predictions are to be made. Must be a matrix.

view

a vector of length nvars, where each entry is an integer describing to which view each feature corresponds.

newcf

Matrix of new values of correction features, if correct.for was specified during model fitting.

predtype

The type of prediction returned by the meta-learner. Allowed values are "response", "link", and "class".

...

Not currently used.

Value

A matrix of predictions.

Author(s)

Wouter van Loon <[e-mail]>

Examples

set.seed(012)
n <- 1000
cors <- seq(0.1,0.7,0.1)
X <- matrix(NA, nrow=n, ncol=length(cors)+1)
X[,1] <- rnorm(n)

for(i in 1:length(cors)){
  X[,i+1] <- X[,1]*cors[i] + rnorm(n, 0, sqrt(1-cors[i]^2))
}

beta <- c(1,0,0,0,0,0,0,0)
eta <- X %*% beta
p <- exp(eta)/(1+exp(eta))
y <- rbinom(n, 1, p)
view_index <- rep(1:(ncol(X)/2), each=2)

fit <- StaPLR(X, y, view_index)
coefficients <- coef(fit)

new_X <- matrix(rnorm(16), nrow=2)
predict(coefficients, new_X, view_index)