mgcv (version 1.1-8)

pdIdnot: Overflow proof pdMat class for multiples of the identity matrix

Description

This set of functions is a modification of the pdMat class pdIdent from library nlme. The modification is to replace the log parameterization used in pdMat with a notLog parameterization, since the latter is much less susceptible to overflow and underflow of the parameters on the original scale. The functions are particularly useful for working with Generalized Additive Mixed Models where variance parameters/smoothing parameters can be very large or very small, so that overflow or underflow can be a problem.

These functions would not normally be called directly, although unlike the pdTens class it is easy to do so.

Usage

pdIdnot(value = numeric(0), form = NULL, 
       nam = NULL, data = sys.frame(sys.parent()))

Arguments

value

Initialization values for parameters. Not normally used.

form

A one sided formula specifying the random effects structure.

nam

a names argument, not normally used with this class.

data

data frame in which to evaluate formula.

Value

• A class pdIdnot object, or related quantities. See the nlme documentation for further details.

Details

Note that while the pdFactor and pdMatrix functions return the inverse of the scaled random effect covariance matrix or its factor, the pdConstruct function is initialised with estimates of the scaled covariance matrix itself.

References

Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Springer

The nlme source code.

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

See Also

te, pdTens, notLog, gamm

Examples

# see gamm