Application of parallel factor analysis model to decompose excitation-emission matrix fluorescence spectra for characterizing sources of water-soluble brown carbon in PM2.5

2020 ◽  
Vol 223 ◽  
pp. 117192 ◽  
Author(s):  
Huanbo Wang ◽  
Leiming Zhang ◽  
Tingting Huo ◽  
Bin Wang ◽  
Fumo Yang ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Fluorescence Spectra ◽  
Parallel Factor Analysis ◽  
Water Soluble ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
Brown Carbon ◽  
Excitation Emission Matrix ◽  
Parallel Factor

scholarly journals A New Algorithm for Computing Disjoint Orthogonal Components in the Parallel Factor Analysis Model with Simulations and Applications to Real-World Data

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2058
Author(s):  
Carlos Martin-Barreiro ◽  
John A. Ramirez-Figueroa ◽  
Xavier Cabezas ◽  
Victor Leiva ◽  
Ana Martin-Casado ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Real World ◽  
Parallel Factor Analysis ◽  
Analysis Model ◽  
Real World Data ◽  
Factor Analysis Model ◽  
World Data ◽  
Orthogonality Constraints ◽  
Orthogonal Components ◽  
Parallel Factor

In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with the parallel factor analysis model. Traditional methods, such as scaling, orthogonality constraints, non-negativity constraints, and sparse techniques, do not guarantee that interpretable loading matrices are obtained in this model. We propose a novel heuristic algorithm that allows simple structure loading matrices to be obtained by calculating disjoint orthogonal components. This algorithm is also an alternative approach for solving the well-known degeneracy problem. We carry out computational experiments by utilizing simulated and real-world data to illustrate the benefits of the proposed algorithm.

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