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A new approach for selecting the number of factors

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  • Chen, Yin-Ping
  • Huang, Hsin-Cheng
  • Tu, I-Ping

Abstract

In factor analysis, it is critical to determine the number of factors. A new approach to select the number of factors based on unbiased risk estimation is introduced. This approach utilizes a concept, called generalized degrees of freedom (GDF), originally proposed for model selection in regression. A data perturbation technique is applied for estimating GDF. Simulation experiments show that the proposed method performs better than some commonly used methods.

Suggested Citation

  • Chen, Yin-Ping & Huang, Hsin-Cheng & Tu, I-Ping, 2010. "A new approach for selecting the number of factors," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2990-2998, December.
  • Handle: RePEc:eee:csdana:v:54:y:2010:i:12:p:2990-2998
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    References listed on IDEAS

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    1. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    2. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    3. Dhrymes, Phoebus J & Friend, Irwin & Gultekin, N Bulent, 1984. " A Critical Reexamination of the Empirical Evidence on the Arbitrage Pricing Theory," Journal of Finance, American Finance Association, vol. 39(2), pages 323-346, June.
    4. Huang, Hsin-Cheng & Chen, Chun-Shu, 2007. "Optimal Geostatistical Model Selection," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1009-1024, September.
    5. Louis Guttman, 1954. "Some necessary conditions for common-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(2), pages 149-161, June.
    6. Wim Krijnen, 2006. "Convergence of Estimates of Unique Variances in Factor Analysis, Based on the Inverse Sample Covariance Matrix," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 193-199, March.
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    Cited by:

    1. Jonathan Bradley & Noel Cressie & Tao Shi, 2015. "Comparing and selecting spatial predictors using local criteria," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 1-28, March.
    2. Jonathan Bradley & Noel Cressie & Tao Shi, 2015. "Rejoinder on: Comparing and selecting spatial predictors using local criteria," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 54-60, March.
    3. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.
    4. repec:eee:intfor:v:34:y:2018:i:2:p:339-354 is not listed on IDEAS

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