vgam.control {VGAM} | R Documentation

## Control function for vgam

### Description

Algorithmic constants and parameters for running `vgam` are set using this function.

### Usage

    vgam.control(all.knots = FALSE, bf.epsilon = 1e-07, bf.maxit = 30,
                 checkwz=TRUE, criterion = names(.min.criterion.VGAM),
                 epsilon = 1e-07, maxit = 30, na.action = na.fail,
                 nk = NULL, save.weight = FALSE, se.fit = TRUE,
                 trace = FALSE, wzepsilon = .Machine$double.eps^0.75,
                 ...)

### Arguments

In the following, we let d be the number of `s` terms in the formula.

`all.knots` | logical indicating if all distinct points of the smoothing variables are to be used as knots. By default, `all.knots=TRUE` for n <= 40, and for n > 40, the number of knots is approximately 40 + (n-40)^0.25. This increases very slowly with n so that the number of knots is approximately between 50 and 60 for large n.
`bf.epsilon` | tolerance used by the modified vector backfitting algorithm for testing convergence. Must be a positive number.
`bf.maxit` | maximum number of iterations allowed in the modified vector backfitting algorithm. Must be a positive integer.
`checkwz` | logical indicating whether the diagonal elements of the working weight matrices should be checked whether they are sufficiently positive, i.e., greater than `wzepsilon`. If not, any values less than `wzepsilon` are replaced with this value.
`criterion` | character variable describing what criterion is to be used to test for convergence. The possibilities are listed in `.min.criterion.VGAM`, but most family functions only implement a few of these.
`epsilon` | positive convergence tolerance epsilon. Roughly speaking, the Newton-Raphson/Fisher-scoring/local-scoring iterations are assumed to have converged when two successive `criterion` values are within `epsilon` of each other.
`maxit` | maximum number of Newton-Raphson/Fisher-scoring/local-scoring iterations allowed.
`na.action` | how to handle missing values. Unlike the SPLUS `gam` function, `vgam` cannot handle `NA`s when smoothing.
`nk` | vector of length d containing positive integers. Recycling is used if necessary. The ith value is the number of B-spline coefficients to be estimated for each component function of the ith `s()` term. `nk` differs from the number of knots by some constant. If specified, `nk` overrides the automatic knot selection procedure.
`save.weight` | logical indicating whether the `weights` slot of a `"vglm"` object will be saved on the object. If not, it will be reconstructed when needed, e.g., `summary`.
`se.fit` | logical indicating whether approximate pointwise standard errors are to be saved on the object. If `TRUE`, then these can be plotted with `plot(..., se=TRUE)`.
`trace` | logical indicating if output should be produced for each iteration.
`wzepsilon` | Small positive number used to test whether the diagonals of the working weight matrices are sufficiently positive.
`...` | other parameters that may be picked up from control functions that are specific to the VGAM family function.

### Details

Most of the control parameters are used within `vgam.fit` and you will have to look at that to understand the full details. Many of the control parameters are used in a similar manner by `vglm.fit` (`vglm`) because the algorithm (IRLS) is very similar.

Setting `save.weight=FALSE` is useful for some models because the `weights` slot of the object is often the largest and so less memory is used to store the object. However, for some VGAM family function, it is necessary to set `save.weight=TRUE` because the `weights` slot cannot be reconstructed later.

### Value

A list with components matching the input names. A little error checking is done, but not much. The list is assigned to the `control` slot of `vgam` objects.

### Note

`vgam` does not implement half-stepsizing, therefore parametric models should be fitted with `vglm`. Also, `vgam` is slower than `vglm` too.

### Author(s)

Thomas W. Yee

### References

Yee, T. W. and Wild, C. J. (1996) Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481–493.

http://www.stat.auckland.ac.nz/~yee

### See Also

`vgam`, `vglm.control`, `vsmooth.spline`, `vglm`.

### Examples

    data(pneumo)
    pneumo = transform(pneumo, let=log(exposure.time))
    vgam(cbind(normal, mild, severe) ~ s(let, df=3), multinomial,
         pneumo, trace=TRUE, eps=1e-4, maxit=10)

[Package VGAM version 0.7-9 Index]