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On uniqueness and selectivity in three-component parallel factor analysis
Analytica Chimica Acta, 2013Unambiguous recovery of profiles is a distinguishable advantage of Parallel Factor Analysis (PARAFAC) as a trilinear model and has made it a promising exploratory tool for data analysis. Linear dependency in profiles destroys trilinearity and will increase ambiguity in the curve resolution of three-way data sets. PARAFAC uniqueness deteriorates totally
Nematollah, Omidikia +2 more
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Parallel factor analysis of ovarian autofluorescence as a cancer diagnostic
Lasers in Surgery and Medicine, 2012AbstractBackground and ObjectivesEndogenous fluorescence from certain amino acids, structural proteins, and enzymatic co‐factors in tissue is altered by carcinogenesis. We evaluate the potential of these changes in fluorescence to predict a diagnosis of malignancy and to estimate the risk of developing ovarian cancer.Study Design/Materials and ...
Ronie, George +3 more
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Parallel Factor Analysis with Constraints on the Configurations: An overview
1998The purpose of the paper is to present an overview of recent developments with respect to the use of constraints in conjunction with the Parallel Factor Analysis PARAFAC model (Harshman, 1970). Constraints and the way they can be incorporated in the estimation process of the model are reviewed. Emphasis is placed on the relatively new triadic algorithm
Kroonenberg, P.M., Heiser, W.J.
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A closed-form solution for Parallel Factor (PARAFAC) Analysis
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008Parallel factor analysis (PARAFAC) is a branch of multi-way signal processing that has received increased attention recently. This is due to the large class of applications as well as the milestone identifiability results demonstrating the superiority to matrix (two-way) analysis approaches.
Florian Roemer, Martin Haardt
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Detecting outlying samples in a parallel factor analysis model
Analytica Chimica Acta, 2011To explore multi-way data, different methods have been proposed. Here, we study the popular PARAFAC (Parallel factor analysis) model, which expresses multi-way data in a more compact way, without ignoring the underlying complex structure. To estimate the score and loading matrices, an alternating least squares procedure is typically used. It is however
Sanne, Engelen, Mia, Hubert
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Biomedical Chromatography, 2021
AbstractPoor chromatographic resolution is one of the main challenges in chromatographic analysis. Partially separated chromatographic peaks frequently occur, due to the nature of analytes and the demand for fast analysis using high flow rates and shorter columns.
Erdal Dinç +2 more
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AbstractPoor chromatographic resolution is one of the main challenges in chromatographic analysis. Partially separated chromatographic peaks frequently occur, due to the nature of analytes and the demand for fast analysis using high flow rates and shorter columns.
Erdal Dinç +2 more
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Maximum likelihood parallel factor analysis (MLPARAFAC)
Journal of Chemometrics, 2003AbstractAlgorithms for carrying out maximum likelihood parallel factor analysis (MLPARAFAC) for three‐way data are described. These algorithms are based on the principle of alternating least squares, but differ from conventional PARAFAC algorithms in that they incorporate measurement error information into the trilinear decomposition.
Lorenzo Vega‐Montoto +1 more
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American Journal of Health Promotion, 2010
Purpose. Exploratory factor analysis is used to identify latent factors for public health interventions. The most popular factor retention criterion, the eigenvalue greater than one (EVG1) rule, leads to the retention of more factors than warranted.
Vivek H, Patil +2 more
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Purpose. Exploratory factor analysis is used to identify latent factors for public health interventions. The most popular factor retention criterion, the eigenvalue greater than one (EVG1) rule, leads to the retention of more factors than warranted.
Vivek H, Patil +2 more
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Spatially constrained parallel factor analysis for semi-blind beamforming
2011 Seventh International Conference on Natural Computation, 2011Parallel factor analysis (PARAFAC) has found numerous applications in blind signal processing, mainly due to its nice identifiability. However, the standard PARAFAC decomposition does not use prior information on the mixing procedure, which could actually be roughly estimated.
Xiao-Feng Gong, Qiu-Hua Lin
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Comprehensive Three-Dimensional Gas Chromatography with Parallel Factor Analysis
Analytical Chemistry, 2007Development of a comprehensive, three-dimensional gas chromatograph (GC3) instrument is described. The instrument utilizes two six-port diaphragm valves as the interfaces between three, in-series capillary columns housed in a standard Agilent 6890 gas chromatograph fitted with a high data acquisition rate flame ionization detector.
Nathanial E, Watson +3 more
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