fit: lcMethod fit process: logic for fitting the method to the processed data

Description

Note: this function should not be called directly, as it is part of the lcMethod fitting process. For fitting an lcMethod object to a dataset, see latrend().

The fit() function of the lcMethod object estimates the model with the evaluated method specification, processed training data, and prepared environment.

Usage

# S4 method for lcMethod
fit(method, data, envir, verbose)

Value

The fitted object inheriting from lcModel.

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 variables generated by prepareData() and preFit().
verbose: A R.utils::Verbose object indicating the level of verbosity.

Implementation

This method should be implemented for all lcMethod subclasses.


setMethod("fit", "lcMethodExample", function(method, data, envir, verbose) {
  # estimate the model or cluster parameters
  coefs <- FIT_CODE
  # create the lcModel object
  new("lcModelExample",
    method = method,
    data = data,
    model = coefs,
    clusterNames = make.clusterNames(method$nClusters)
  )
})

Fitting procedure

Each lcMethod subclass defines a type of methods in terms of a series of steps for estimating the method. These steps, as part of the fitting procedure, are executed by latrend() in the following order:

compose(): Evaluate and finalize the method argument values.
validate(): Check the validity of the method argument values in relation to the dataset.
prepareData(): Process the training data for fitting.
preFit(): Prepare environment for estimation, independent of training data.
fit(): Estimate the specified method on the training data, outputting an object inheriting from lcModel.
postFit(): Post-process the outputted lcModel object.

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