lcMethod estimation step: method preparation logic

Note: this function should not be called directly, as it is part of the lcMethod estimation procedure. For fitting an lcMethod object to a dataset, use the latrend() function or one of the other standard estimation functions.

The preFit() function of the lcMethod object performs preparatory work that is needed for fitting the method but should not be counted towards the method estimation time. The work is added to the provided environment, allowing the fit() function to make use of the prepared work.

preFit(method, data, envir, verbose, ...)

# S4 method for class 'lcMethod'
preFit(method, data, envir, verbose)

Arguments

method

An object inheriting from lcMethod with all its arguments having been evaluated and finalized.

data

A data.frame representing the transformed training data.

envir

The environment containing additional data variables returned by prepareData().

verbose

A R.utils::Verbose object indicating the level of verbosity.

...

Not used.

Value

The updated environment that will be passed to fit().

Implementation

setMethod("preFit", "lcMethodExample", function(method, data, envir, verbose) {
  # update envir with additional computed work
  envir$x <- INTENSIVE_OPERATION
  return(envir)
})

Estimation procedure

The steps for estimating a lcMethod object are defined and executed as follows:

1. compose(): Evaluate and finalize the method argument values.

2. validate(): Check the validity of the method argument values in relation to the dataset.

3. prepareData(): Process the training data for fitting.

4. preFit(): Prepare environment for estimation, independent of training data.

5. fit(): Estimate the specified method on the training data, outputting an object inheriting from lcModel.

6. postFit(): Post-process the outputted lcModel object.

The result of the fitting procedure is an lcModel object that inherits from the lcModel class.