American Journal of Theoretical and Applied Statistics

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Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach

Received: 25 September 2013    Accepted:     Published: 10 November 2013
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Abstract

DOI 10.11648/j.ajtas.20130206.16
Published in American Journal of Theoretical and Applied Statistics (Volume 2, Issue 6, November 2013)
Page(s) 191-201
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Factor Analysis, Factor Rotation, Maximum Likelihood Estimation Method, Akaike, Schwarz, Hannan Quinne Information Criteria

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.
Author Information
  • Department of Mathematics and Statistics Federal Polytechnic Nekede, Owerri Imo State

  • Department of Statistics, Imo State University, Owerri, PMB 2000, Owerri Nigeria

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  • APA Style

    Nwosu F. Dozie, Onyeagu, Sidney I., Osuji, George A., et al. (2013). Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach. American Journal of Theoretical and Applied Statistics, 2(6), 191-201. https://doi.org/10.11648/j.ajtas.20130206.16

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    ACS Style

    Nwosu F. Dozie; Onyeagu; Sidney I.; Osuji; George A., et al. Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach. Am. J. Theor. Appl. Stat. 2013, 2(6), 191-201. doi: 10.11648/j.ajtas.20130206.16

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    AMA Style

    Nwosu F. Dozie, Onyeagu, Sidney I., Osuji, George A., et al. Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach. Am J Theor Appl Stat. 2013;2(6):191-201. doi: 10.11648/j.ajtas.20130206.16

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  • @article{10.11648/j.ajtas.20130206.16,
      author = {Nwosu F. Dozie and Onyeagu and Sidney I. and Osuji and George A. and Ekezie Dan Dan},
      title = {Method of Maximum Likelihood Estimation of Optimal Number of Factors: An Information Criteria Approach},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {2},
      number = {6},
      pages = {191-201},
      doi = {10.11648/j.ajtas.20130206.16},
      url = {https://doi.org/10.11648/j.ajtas.20130206.16},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20130206.16},
      abstract = {},
     year = {2013}
    }
    

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