D. B. Rowe. Correlated Bayesian Factor Analysis. PhD thesis, Department of Statistics, University of California, Riverside, Riverside, CA 92521, December 1998. Home/Search Document Details and Download
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On Using the Sample Mean in Bayesian Factor Analysis - Rowe Self-citation (Rowe) (Correct)
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D. B. Rowe. Correlated Bayesian Factor Analysis. PhD thesis, Department of Statistics, University of California, Riverside, Riverside, CA 92521, December 1998.
On Estimating The Mean In Bayesian Factor Analysis - Rowe (2000) Self-citation (Rowe) (Correct)
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D. B. Rowe. Correlated Bayesian Factor Analysis. PhD thesis, De- partment of Statistics, University of California, Riverside, CA 92521, 1998.
A Bayesian Factor Analysis Model With Generalized Prior Information - Rowe (2001) Self-citation (Rowe) (Correct)
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D. B. Rowe. Correlated Bayesian Factor Analysis. PhD thesis, Department of Statistics, University of California, Riverside, CA 92521, December 1998.
Incorporating Prior Knowledge Regarding the Mean in Bayesian.. - Rowe (2001) Self-citation (Rowe) (Correct)
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D. B. Rowe. Correlated Bayesian Factor Analysis. PhD thesis, Department of Statistics, University of California, Riverside, CA 92521, December 1998. 16
A Bayesian Approach to Blind Source Separation - Rowe (1999) (2 citations) Self-citation (Rowe) (Correct)
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D. B. Rowe, Correlated Bayesian Factor Analysis, Ph.D. thesis, Department of Statistics, University of California, Riverside, 1998.
A General Bayesian Approach To Blind Source Separation With.. - Rowe (1999) Self-citation (Rowe) (Correct)
....i and i 0 is given by the m Theta m matrix cov(s i ; s i 0 j Theta; m) Theta ii 0 : The error covariance matrix and the source correlation matrices can be simplified by specifing a particular structure, thereby reducing the number of distinct parameters and the required computation. Rowe (1998) in the context of Bayesian factor analysis has considered separable and matrix intraclass covariance matrices. The separable covariance correlation matrices for the errors and sources is Omega j 0 B B B B B B B OE 11 Psi OE 12 Psi Delta Delta Delta OE 1n Psi OE 22 Psi . ....
....= ii 0 R: Separable covariance matrices have a wide variety of applications, for example in time series. If Phi were a first order Markov correlation matrix, with elements given by ae ji Gammai 0 j for row i and column i 0 then Omega reprents a first order vector autoressive structure. Rowe (1998) has considered matrix intraclass covariance correlation structures, given by Omega = 0 B B B B B B B Psi Upsilon Delta Delta Delta Upsilon Psi . Upsilon Psi 1 C C C C C C C A ; Psi 0; Upsilon 0 (2.1) and Theta = 0 B B B B B B B R P Delta Delta Delta P R . ....
Rowe, D. B. (1998). "Correlated Bayesian Factor Analysis," Ph.D. Thesis, Department of Statistics, University of California, Riverside.
Bayesian Blind Source Separation - Rowe (1999) (2 citations) Self-citation (Rowe) (Correct)
No context found.
D. B. Rowe, Correlated Bayesian Factor Analysis, Ph.D. thesis, Department of Statistics, University of California, Riverside, 1998.
A Bayesian Approach to Blind Source Separation - Rowe (1999) (2 citations) (Correct)
No context found.
D. B. Rowe, Correlated Bayesian Factor Analysis,Ph.D.thesis,Depart- ment of Statistics, University of California, Riverside, 1998. 30
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