Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach
American Journal of Theoretical and Applied Statistics
Volume 2, Issue 6, November 2013, Pages: 191-201
Received: Sep. 25, 2013; Published: Nov. 10, 2013
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Authors
Nwosu F. Dozie, Department of Mathematics and Statistics Federal Polytechnic Nekede, Owerri Imo State
Onyeagu, Sidney I., Department of Statistics Nnamdi Azikiwe University Awka, Anambra Stat
Osuji, George A., Department of Statistics Nnamdi Azikiwe University Awka, Anambra Stat
Ekezie Dan Dan, Department of Statistics, Imo State University, Owerri, PMB 2000, Owerri Nigeria
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Keywords
Factor Analysis, Factor Rotation, Maximum Likelihood Estimation Method, Akaike, Schwarz, Hannan Quinne Information Criteria
To cite this article
Nwosu F. Dozie, Onyeagu, Sidney I., Osuji, George A., Ekezie Dan Dan, Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach, American Journal of Theoretical and Applied Statistics. Vol. 2, No. 6, 2013, pp. 191-201. doi: 10.11648/j.ajtas.20130206.16
References
[1]
Akaike, H. (1973). Information Theory and Extension of the Maximum Likelihood Principle; Second International Symposium on Information Theory (B.N. Petrov and F. Csaki, Eds.). Budapest Hungary: Akademia Kiado, 267-281
[2]
Comrey, A.L., and Lee, H.B. (1992). A First Course in Factor Analysis (2nd Ed.). Hillsdale, NJ: Erlbaum.
[3]
Harman, H.H. (1976). Modern Factor Analysis (3rd Ed.). Chicago: The University of Chicago Press.
[4]
Johnson, R.A., and Wichern, D.W. (2007). Applied Multivariate Statistical Analysis (6th Ed.). Prentics Hall, Englewood Cliffs, New Jersey.
[5]
Onyeagu, S.I. (2003). A First Course in Multivariate Statistical Analysis (1st Ed.). Mega Concept Publishers.
[6]
Schwarz,G.(1978). Estimating the Dimension of a Model. Annals of Statistics 6, 461-464.
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