surveillance (version 1.7-0)

twinstim_update: 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. It will modify the original control.siaf using modifyList.

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.

...

Additional arguments to the call, or arguments with changed values.

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.

See Also

update.default

Examples

data("imdepi")
data("imdepifit")

## add another epidemic covariate (but fix siaf-parameter for speed)
imdepifit2 <- update(imdepifit, epidemic = ~. + log(popdensity),
                     optim.args = list(fixed="e.siaf.1"), cumCIF=FALSE)
  
## compare by AIC
AIC(imdepifit, imdepifit2)

if (surveillance.options("allExamples")) {
  ## enrich the fit by the model environment
  imdepifit <- update(imdepifit, model=TRUE)
  ## this enables, e.g., intensityplot()s and untrimmed R0 estimates
}