Sparse exploratory factor analysis

Fontanella, Sara; Trendafilov, Nickolay and Adachi, Kohei (2014). Sparse exploratory factor analysis. In: Proceedings of COMPSTAT 2014: 21st International Conference on Computational Statistics, pp. 281–288.

URL: http://compstat2014.org/auxil/Proceedings-COMPSTAT...

Abstract

Sparse principal component analysis is a very active research area in the last decade. In the same time, there are very few works on sparse factor analysis. We propose a new contribution to the area by exploring a procedure for sparse factor analysis where the unknown parameters are found simultaneously.

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About

• Item ORO ID
• 41226
• Item Type
• Conference or Workshop Item
• ISBN
• 2-8399-1347-X, 978-2-8399-1347-8
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  Sparse factor analysis with application to large data sets	RPG--2013--211	Leverhulme Trust

• Keywords
• ℓ1 penalties; matrix manifolds; projected gradients
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2014 The International Statistical Institute/International Association for Statistical Computing
• Related URLs
• • http://compstat2014.org/(Other)
• Depositing User
• Nickolay Trendafilov