The Open UniversitySkip to content
 

A majorization algorithm for simultaneous parameter estimation in robust exploratory factor analysis

Unkel, S. and Trendafilov, N. T. (2010). A majorization algorithm for simultaneous parameter estimation in robust exploratory factor analysis. Computational Statistics and Data Analysis, 54(12) pp. 3348–3358.

URL: http://dx.doi.org/10.1016/j.csda.2010.02.003
Google Scholar: Look up in Google Scholar

Abstract

A new approach for fitting the exploratory factor analysis (EFA) model is considered. The EFA model is fitted directly to the data matrix by minimizing a weighted least squares (WLS) goodness-of-fit measure. The WLS fitting problem is solved by iteratively performing unweighted least squares fitting of the same model. A convergent reweighted least squares algorithm based on iterative majorization is developed. The influence of large residuals in the loss function is curbed using Huber’s criterion. This procedure leads to robust EFA that can resist the effect of outliers in the data. Applications to real and simulated data illustrate the performance of the proposed approach.

Item Type: Journal Article
Copyright Holders: 2010 Elsevier B.V.
ISSN: 0167-9473
Keywords: factor analysis; procrustes problems; reweighted least squares; constrained optimization; iterative majorization; robust estimation; huber function
Academic Unit/Department: Mathematics, Computing and Technology
Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 24146
Depositing User: Steffen Unkel
Date Deposited: 28 Oct 2010 11:08
Last Modified: 03 Dec 2012 12:05
URI: http://oro.open.ac.uk/id/eprint/24146
Share this page:

Actions (login may be required)

View Item
Report issue / request change

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk