Comparing a new algorithm with the classic methods for estimating the number of factors
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This paper presents and compares a new algorithm for finding the number of factors in a data analytic model. After we describe the new method, called NUMFACT, we compare it with standard methods for finding the number of factors to use in a model. The standard methods that we compare NUMFACT with are Malinowski's indicator function, Wold's cross-validation approach, Bartlett's test, scree plots, the rule-of-one, and using the number of factors (eigenvectors) needed to explain 90% of the trace of a correlation matrix. Using a diverse set of real applications, NUMFACT is shown to be the clear method of choice.
author list (cited authors)
Henry, R. C., Park, E. S., & Spiegelman, C. H.