R: Predict method for TDboost Model Fits

predict.TDboost {TDboost} | R Documentation

## Predict method for TDboost Model Fits

### Description

Predicted values based on an TDboost Tweedie regression model object

### Usage

    ## S3 method for class 'TDboost'
    predict(object,
            newdata,
            n.trees,
            single.tree=FALSE,
    		  type=c("response","link"),
            ...)

### Arguments

`object` | Object of class inheriting from (`TDboost.object`)
`newdata` | Data frame of observations for which to make predictions
`n.trees` | Number of trees used in the prediction. `n.trees` may be a vector in which case predictions are returned for each iteration specified
`single.tree` | If `single.tree=TRUE` then `predict.TDboost` returns only the predictions from tree(s) `n.trees`
`type` | 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

### Details

`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.

### Value

Returns a vector of predictions. By default the predictions are on the scale of f(x).

### Author(s)

Yi Yang yi.yang6@mcgill.ca, Wei Qian wxqsma@rit.edu and Hui Zou hzou@stat.umn.edu

### See Also

`TDboost`, `TDboost.object`

[Package TDboost version 1.2 Index]