Predicted values based on an TDboost Tweedie regression model object
# S3 method for TDboost
predict(object,
newdata,
n.trees,
single.tree=FALSE,
type=c("response","link"),
...)
Returns a vector of predictions. By default the predictions are on the scale of f(x).
Object of class inheriting from (TDboost.object)
Data frame of observations for which to make predictions
Number of trees used in the prediction. n.trees may
be a vector in which case predictions are returned for each
iteration specified
If single.tree=TRUE then predict.TDboost returns
only the predictions from tree(s) n.trees
type of prediction required.
Type "response" gives predicted response mu(x) = E(Y|X=x) for the regression problems. It is the default.
Type "link" gives the linear predictors x*b = log(mu(x)) = log(E(Y|X=x)) for the regression problems.
further arguments passed to or from other methods
Yi Yang yi.yang6@mcgill.ca, Wei Qian wxqsma@rit.edu and Hui Zou hzou@stat.umn.edu
predict.TDboost produces predicted values for each observation in newdata using the the first n.trees iterations of the boosting sequence. If n.trees is a vector than the result is a matrix with each column representing the predictions from TDboost models with n.trees[1] iterations, n.trees[2] iterations, and so on.
The predictions from TDboost do not include the offset term. The user may add the value of the offset to the predicted value if desired.
If object was fit using TDboost.fit there will be no
Terms component. Therefore, the user has greater responsibility to make
sure that newdata is of the same format (order and number of variables)
as the one originally used to fit the model.
TDboost, TDboost.object