Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415966 | Computational Statistics & Data Analysis | 2010 | 9 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Yin-Ping Chen, Hsin-Cheng Huang, I-Ping Tu,