Predict.matrix.cr.smooth {mgcv} | R Documentation

## Predict matrix method functions

### Description

The various built in smooth classes for use with `gam` have associate `Predict.matrix` method functions to enable prediction from the fitted model.

### Usage

    ## S3 method for class 'cr.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'cs.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'cyclic.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'pspline.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tensor.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tprs.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'ts.smooth'
    Predict.matrix(object, data)

### Arguments

`object` | a smooth object, usually generated by a `smooth.construct` method having processed a smooth specification object generated by an `s` or `te` term in a `gam` formula.
`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 `smooth.construct` and `smooth.construct2`

.

### Details

The Predict matrix function is not normally called directly, but is rather used internally by `predict.gam` etc. to predict from a fitted `gam` model. See `Predict.matrix` for more details, or the specific `smooth.construct` pages for details on a particular smooth class.

### Value

A matrix mapping the coeffients for the smooth term to its values at the supplied data values.

### Author(s)

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

### References

Wood S.N. (2006) Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press.

### Examples

    ## see smooth.construct

[Package mgcv version 1.7-18 Index]