Detecting outlying samples in a parallel factor analysis model

2011 ◽  
Vol 705 (1-2) ◽  
pp. 155-165 ◽  
Author(s):  
Sanne Engelen ◽  
Mia Hubert
Keyword(s):  
Factor Analysis ◽  
Parallel Factor Analysis ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
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.

scholarly journals Joint 2D Direction-of-Arrival and Range Estimation for Nonstationary Sources

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jian Chen ◽  
Hui Zhao ◽  
Xiaoying Sun ◽  
Guohong Liu
Keyword(s):  
Factor Analysis ◽  
Near Field ◽  
Direction Of Arrival ◽  
Parallel Factor Analysis ◽  
Observation Data ◽  
Factor Analysis Model ◽  
Time Frequency ◽  
Multidimensional Search ◽  
Parallel Factor ◽  
Nonstationary Sources

Passive localization of nonstationary sources in the spherical coordinates (azimuth, elevation, and range) is considered, and a parallel factor analysis based method is addressed for the near-field parameter estimation problem. In this scheme, a parallel factor analysis model is firstly constructed by computing five time-frequency distribution matrices of the properly chosen observation data. In addition, the uniqueness of the constructed model is proved, and both the two-dimensional (2D) direction-of-arrival (DOA) and range can be jointly obtained via trilinear alternating least squares regression (TALS). The investigated algorithm is well suitable for near-field nonstationary source localization and does not require parameter-pairing or multidimensional search. Several simulation examples confirm the effectiveness of the proposed algorithm.

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