predict.Bayenet {Bayenet}

make predictions from a Bayenet object

Description

make predictions from a Bayenet object

Usage

## S3 method for class 'Bayenet'
predict(object, X.new, clin.new, Y.new, ...)

Arguments

object

Bayenet object.

X.new

a matrix of new values for X at which predictions are to be made.

clin.new

a vector or matrix of new values for clin at which predictions are to be made.

Y.new

a vector of the response of new observations. If provided, the prediction error will be computed based on Y.new.

...

other predict arguments

Details

X.new must have the same number of columns as X used for fitting the model. If clin was provided when fit the model, clin.new must not be NULL, and vice versa. The predictions are made based on the posterior estimates of coefficients in the Bayenet object. Note that the effects of clinical factors are not subject to selection.

If Y.new is provided, the prediction error will be computed. For robust methods, the prediction mean absolute deviations (PMAD) will be computed. For non-robust methods, the prediction mean squared error (PMSE) will be computed.

Value

an object of class ‘Bayenet.pred’ is returned, which is a list with components:

error

prediction error. error is NULL is Y.new=NULL.

y.pred

predicted values of the new observations.

See Also

Bayenet

Examples

data(dat)
test=sample((1:nrow(X)), floor(nrow(X)/5))
fit=Bayenet(X[-test,], Y[-test], clin[-test,], max.steps=500,penalty="lasso")
predict(fit, X[test,], clin[test,], Y[test,])