Folch Fortuny, Abel; Arteaga Moreno, Francisco Javier; Ferrer, Alberto(Wiley, 2016-07)
Maximum likelihood principal component analysis (MLPCA) was originally proposed to incorporate measurement error variance information in principal component analysis (PCA) models. MLPCA can be used to fit PCA models in the ...
Folch Fortuny, Abel; Arteaga Moreno, Francisco Javier; Ferrer, Alberto(Elsevier, 2016-03-15)
[EN] Here we introduce a graphical user-friendly interface to deal with missing values called Missing Data Imputation (MDI) Toolbox. This MATLAB toolbox allows imputing missing values, following missing completely at random ...
Folch-Fortuny, Abel; ARTEAGA MORENO, FRANCISCO JAVIER; Ferrer Riquelme, Alberto José(Elsevier, 2015-08-15)
[EN] This paper introduces new methods for building principal component analysis (PCA) models with missing data: projection to the model plane (PMP), known data regression (KDR), KDR with principal component regression ...