Comparing a new algorithm with the classic methods for estimating the number of factors

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 Malinowskiʹs indicator function, Woldʹs cross-validation approach, Bartlettʹs 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.