prune_mfpc {multifamm} | R Documentation |
Prune the MFPC object to include only a prespecified level of explained var
Description
This is an internal function contained in the multiFAMM function. This function takes the MFPCA object and decides how many functional principal components are to be included in the model.
Usage
prune_mfpc(MFPC, mfpc_cutoff, model_list, mfpc_cut_method, number_mfpc,
mfpca_info)
Arguments
MFPC |
List containing MFPC objects for each variance component as given by the function conduct_mfpca() |
mfpc_cutoff |
Pre-specified level of explained variance of results of MFPCA. Defaults to 0.95. |
model_list |
List containing sparseFLMM objects for each dimension as given by the output of apply_sparseFLMM() |
mfpc_cut_method |
Method to determine the level of explained variance
|
number_mfpc |
List containing the number of mfPCs needed for each variance component e.g. list("E" = x, "B" = y). |
mfpca_info |
Object containing all the neccessary information for the MFPCA. List as given by the output of prepare_mfpca(). |