# Predict Method for addreg Fits

### Description

Obtains predictions from a fitted `addreg`

object.

### Usage

1 2 3 |

### Arguments

`object` |
a fitted object of class inheriting from |

`newdata` |
optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used. |

`type` |
the type of prediction required. The default is on the scale of the linear predictors;
the alternative The value of this argument can be abbreviated. |

`terms` |
with |

`na.action` |
function determining what should be done with missing values in |

`checkminmax` |
logical indicating whether or not values of continuous covariates in |

`...` |
further arguments passed to or from other methods. |

### Details

If `newdata`

is omitted the predictions are based on the data used for the fit.
In that case how cases with missing values in the original fit are treated is determined by the
`na.action`

argument of that fit. If `na.action = na.omit`

, omitted cases
will not appear in the residuals; if `na.action = na.exclude`

they will
appear, with residual value `NA`

. See also `napredict`

.

### Value

A vector or matrix of predictions. For `type = "terms"`

, this is a matrix with
a column per term, and may have an attribute `"constant"`

.

### Note

Variables are first looked for in `newdata`

and then searched for in the usual
way (which will include the environment of the formula used in the fit). A warning
will be given if the variables found are not of the same length as those in
`newdata`

if it was supplied.

### Author(s)

Mark W. Donoghoe Mark.Donoghoe@mq.edu.au

### See Also

`addreg`

`predict.glm`

for the equivalent method for models fit using `glm`

.

### Examples

1 | ```
## For an example, see example(addreg)
``` |