twinstim_update {surveillance}

update-method for "twinstim"

Description

Update and (by default) re-fit a "twinstim". This method is especially useful if one wants to add the model environment (which is required for some methods) to a fitted model object a posteriori.

Usage

## S3 method for class 'twinstim'
update(object, endemic, epidemic,
       control.siaf, optim.args, model,
       ..., use.estimates = TRUE, evaluate = TRUE)

Arguments

object

a previous "twinstim" fit.

endemic, epidemic

changes to the formulae – see update.formula and twinstim.

control.siaf

a list (see twinstim) to replace the given elements in the original control.siaf list. If NULL, the original list of control arguments is removed from the call, i.e., the defaults are used in twinstim.

optim.args

see twinstim. If a list, it will modify the original optim.args using modifyList.

model

see twinstim. If this is the only argument to update, re-fitting is cleverly circumvented. Enriching the fit by the model environment is, e.g., required for intensityplot.twinstim.

...

Additional arguments to the call, or arguments with changed values.
If start values are specified, they need to be in the same format as in the original call object$call$start, which is either a named list of named numeric vectors or a named numeric vector; see the argument description in twinstim.

use.estimates

logical indicating if the estimates of object should be used as initial values for the new fit (in the start argument of twinstim). Defaults to TRUE.

evaluate

If TRUE (default), evaluate the new call else return the call.

Value

If evaluate = TRUE the re-fitted object, otherwise the updated call.

Author(s)

Sebastian Meyer

Inspiration and some pieces of code originate from update.default by the R Core Team.

See Also

update.default

Examples

data("imdepi", "imdepifit")

## add another epidemic covariate
## (but fix siaf-parameter so that this example runs quickly)
imdepifit2 <- update(imdepifit, epidemic = ~. + log(popdensity),
                     optim.args = list(fixed="e.siaf.1"))

## compare by AIC
AIC(imdepifit, imdepifit2)