Helper function for custom lcModel classes implementing fitted.lcModel()

A helper function for implementing the fitted.lcModel() method as part of your own lcModel class, ensuring the correct output type and format (see the Value section). Note that this function has no use outside of implementing fitted.lcModel.

The function makes it easier to implement fitted.lcModel based on existing implementations that may output their results in different data formats. Furthermore, the function checks whether the input data is valid.

The prediction ordering depends on the ordering of the data observations that was used for fitting the lcModel.

By default, transformFitted() accepts one of the following inputs:

data.frame: A data.frame in long format providing a cluster-specific prediction for each observation per row, with column names "Fit" and "Cluster". This data.frame therefore has nobs(object) * nClusters(object) rows.
matrix: An N-by-K matrix where each row provides the cluster-specific predictions for the respective observation. Here, N = nrow(model.data(object)) and K = nClusters(object).
list: A list of cluster-specific prediction vectors. Each prediction vector should be of length nrow(model.data(object)). The overall (named) list of cluster-specific prediction vectors is of length nClusters(object).

Users can implement support for other prediction formats by defining the transformFitted method with other signatures.

transformFitted(pred, model, clusters)

# S4 method for NULL,lcModel
transformFitted(pred, model, clusters = NULL)

# S4 method for matrix,lcModel
transformFitted(pred, model, clusters = NULL)

# S4 method for list,lcModel
transformFitted(pred, model, clusters = NULL)

# S4 method for data.frame,lcModel
transformFitted(pred, model, clusters = NULL)

Arguments

pred: The cluster-specific predictions for each observation
model: The lcModel by which the prediction was made.
clusters: The trajectory cluster assignment per observation. Optional.

Value

If the clusters argument was specified, a vector of fitted values conditional on the given cluster assignment. Else, a matrix with the fitted values per cluster per column.

Example implementation

A typical implementation of fitted.lcModel() for your own lcModel class would have the following format:


fitted.lcModelExample <- function(object,
 clusters = trajectoryAssignments(object)) {
  # computations of the fitted values per cluster here
  predictionMatrix <- CODE_HERE
  transformFitted(pred = predictionMatrix, model = object, clusters = clusters)
}

For a complete and runnable example, see the custom models vignette accessible via vignette("custom", package = "latrend").