A Review of Nonlinear Factor Analysis Statistical Methods

Factor analysis that has been used most frequently in practice can be characterized as linear analysis. Linear factor analysis explores a linear factor space underlying multivariate observations or addresses linear relationships between observations and latent factors. However, the basic factor analysis concept is valid without this limitation to linear analyses. Hence, it is natural to advance factor analysis beyond the linear restriction, i.e., to consider nonlinear or general factor analysis. In fact, the notion of nonlinear factor analysis was introduced very early. But, as in the linear case, the development of statistical methods lagged that of the concept considerably, and has only recently started to receive broad attention. This paper reviews such methodological development for nonlinear factor analysis.

By: Melanie M. Wall, Yasuo Amemiya

Published in: RC23392 in 2004


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