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.
# S4 method for lcMethod
fit(method, data, envir, verbose)An object inheriting from lcMethod with all its arguments having been evaluated and finalized.
A data.frame representing the transformed training data.
The environment containing variables generated by prepareData() and preFit().
A R.utils::Verbose object indicating the level of verbosity.
The fitted object inheriting from lcModel.
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)
)
})
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.