smoothCon {mgcv} | R Documentation |

## Prediction/Construction wrapper functions for GAM smooth terms

### Description

Wrapper functions for construction of and prediction from smooth
terms in a GAM. The purpose of the wrappers is to allow user-transparant
re-parameterization of smooth terms, in order to allow identifiability
constraints to be absorbed into the parameterization of each term, if required.

### Usage

smoothCon(object,data,knots,absorb.cons=FALSE,scale.penalty=TRUE)
PredictMat(object,data)

### Arguments

`object` |
is a smooth specification object or a smooth object. |

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

`knots` |
An optional data frame supplying any knot locations to be
supplied for basis construction. |

`absorb.cons` |
Set to `TRUE` in order to have identifiability
constraints absorbed into the basis. |

`scale.penalty` |
should the penalty coefficient matrix be scaled to have
approximately the same `size' as the inner product of the terms model matrix
with itself? This can improve the performance of `gamm` fitting. |

### Details

These wrapper functions exist to allow smooths specified using
`smooth.construct`

and `Predict.matrix`

method
functions to be re-parameterized so that identifiability constraints are no
longer required in fitting. This is done in a user transparent
manner, but is typically of no importance in use of GAMs.

The parameterization used by `gam`

can be controlled via
`gam.control`

.

### Value

From `smoothCon`

a `smooth`

object returned by the
appropriate `smooth.construct`

method function. If constraints are
to be absorbed then the object will have an attributes `"qrc"`

and
`"nCons"`

, the qr decomposition of the constraint matrix (returned by
`qr`

) and the number of constraints, respectively: these are used in
the re-parameterization.

For `predictMat`

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`

.

### Author(s)

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

### References

http://www.stats.gla.ac.uk/~simon/

### See Also

`gam.control`

,
`smooth.construct`

, `Predict.matrix`

[Package

*mgcv* version 1.3-12

Index]