pdIdnot {mgcv} | R Documentation

## 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 `notLog2` parameterization, since the latter avoids indefiniteness in the likelihood and associated convergence problems: the parameters also relate to variances rather than standard deviations, for consistency with the `pdTens` class. 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.

### 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.

### Value

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

### Author(s)

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

### References

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

The `nlme` source code.

http://www.maths.bath.ac.uk/~sw283/

### See Also

`te`, `pdTens`, `notLog2`, `gamm`

### Examples

    # see gamm

[Package mgcv version 1.3-17 Index]