parafac4microbiome 1.1.2

parafac4microbiome 1.1.1

vanderPloeg2024 now contains all datasets from the original paper.
The contents in /data-raw/ are updated to better organize the studies.
The Frobenius norm of the tensor is now collapsed into the subject mode (was the O-norm).
Fixed an issue where flipLoadings() would not flip any of the modes if there was evidence that all three modes should be flipped.
Fixed an issue where flipLoadings() would not work when one model was provided.
All vignettes are updated to better reflect the updated functions for this version.

Minor changes to tests for parafac_gradient to make them more robust towards various platforms checked by CRAN.

Further rework of importPhyloseq, importTreeSummarizedExperiment and importMicrobiotaProcess to meet CRAN requirements.

Streamlined examples in importPhyloseq, importTreeSummarizedExperiment and importMicrobiotaProcess.

Edited DESCRIPTION to meet CRAN requirements.
importPhyloseq was modified to use rTensor-based cube folding instead of a for-loop.
importTreeSummarizedExperiment was modified to use rTensor-based cube folding instead of a for-loop.
importMicrobiotaProcess was modified to use rTensor-based cube folding instead of a for-loop.

‘parafac’ is now capable of running an all-at-once optimization using the methods=“opt” parameter. For now, the default remains methods=“als” (i.e. the ALS algorithm) because it converges faster to a similar solution.
importPhyloseq allows the user to import a phyloseq object for parafac modelling.
importTreeSummarizedExperiment allows the user to import a TreeSummarizedExperiment object for parafac modelling.
importMicrobiotaProcess allows the user to import a MicrobiotaProcess object for parafac modelling.
The text in the vignettes were updated to better reflect the changes per version 0.1.0.
The readme and vignettes figures now use sign flipping to make comparison with the paper easier.
Some documentation and testing changes anticipating a CRAN release.

parafac is now a custom function based on an ALS algorithm allowing for much more output (see documentation).
initializePARAFAC initializes the input vectors either randomly on based on a best-guess SVD model of the unfolded array.
parafac_core_als contains this ALS algorithm.
parafac_fun calculates the loss of a parafac model in anticipation of an all-at-once optimization implementation.
assessNumComponents and checkModelStability have been renamed into assessModelQuality and assessModelStability respectively to clarify their use.
checkModelStability now works with a minimum and maximum number of components.
checkModelStability reports Factor Match Score in a plot.
calculateFMS calculates pairwise Factor Match Scores for a list of model objects.
parafac, multiwayCenter, multiwayScale and multiwayCLR are now based on the new rTensor dependency for tensor unfolding
plotOverallTCCs has been merged with plotModelTCCs.
Many bugfixes. PARAFAC model solutions should be more stable as a result.
Many documentation changes across the board. Overall, the use case per function should be much clearer.
Vignettes are updated to reflect and utilize the new changes.
Removed dependency: paramGUI