Predict.matrix {mgcv} | R Documentation |

## Prediction methods for smooth terms in a GAM

### Description

Takes `smooth`

objects produced by `smooth.construct`

methods and obtains the matrix mapping
the parameters associated with such a smooth to the predicted values of the smooth at a set of new covariate values.

In practice this method is often called via the wrapper function `PredictMat`

.

### Usage

```
Predict.matrix(object,data)
Predict.matrix2(object,data)
```

### Arguments

`object` |
is a smooth object produced by a |

`data` |
A data frame containing the values of the (named) covariates at which the smooth term is to be
evaluated. Exact requirements are as for |

.

### Details

Smooth terms in a GAM formula are turned into smooth specification objects of
class `xx.smooth.spec`

during processing of the formula. Each of these objects is
converted to a smooth object using an appropriate `smooth.construct`

function. The `Predict.matrix`

functions are used to obtain the matrix that will map the parameters associated with a smooth term to
the predicted values for the term at new covariate values.

Note that new smooth classes can be added by writing a new `smooth.construct`

method function and a
corresponding `Predict.matrix`

method function: see the example code provided for
`smooth.construct`

for details.

### Value

A matrix which will map the parameters associated with the smooth to the vector of values of the smooth
evaluated at the covariate values given in `object`

. If the smooth class
is one which generates offsets the corresponding offset is returned as
attribute `"offset"`

of the matrix.

### Author(s)

Simon N. Wood simon.wood@r-project.org

### References

Wood S.N. (2017) Generalized Additive Models: An Introduction with R (2nd edition). Chapman and Hall/CRC Press.

### See Also

`gam`

,`gamm`

,
`smooth.construct`

, `PredictMat`

### Examples

```
# See smooth.construct examples
```

*mgcv*version 1.9-1 Index]