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)

Arguments

object is a smooth object produced by a smooth.construct method function. The object contains all the information required to specify the basis for a term of its class, and this information is used by the appropriate Predict.matrix function to produce a prediction matrix for new covariate values. Further details are given in smooth.construct.
data A data frame containing the values of the (named) covariates at which the smooth term is to be evaluated.

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.

Author(s)

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

References

Wood, S.N. (2000) Modelling and Smoothing Parameter Estimation with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428

Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114

Wood, S.N. (in press) Stable and efficient multiple smoothing parameter estimation for generalized additive models. J. Amer. Statist. Ass.

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

See Also

gam,gamm, smooth.construct, PredictMat

Examples

# See smooth.construct examples

[Package mgcv version 1.2-3 Index]