Estimation of an oblique structure via penalized likelihood factor analysis

Kei Hirose, Michio Yamamoto

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

The problem of sparse estimation via a lasso-type penalized likelihood procedure in a factor analysis model is considered. Typically, model estimation assumes that the common factors are orthogonal (i.e., uncorrelated). However, if the common factors are correlated, the lasso-type penalization method based on the orthogonal model frequently estimates an erroneous model. To overcome this problem, factor correlations are incorporated into the model. Together with parameters in the orthogonal model, these correlations are estimated by a maximum penalized likelihood procedure. Entire solutions are computed by the EM algorithm with a coordinate descent, enabling the application of a wide variety of convex and nonconvex penalties. The proposed method is applicable even when the number of variables exceeds that of observations. The effectiveness of the proposed strategy is evaluated by Monte Carlo simulations, and its utility is demonstrated through real data analysis.

Original languageEnglish
Pages (from-to)120-132
Number of pages13
JournalComputational Statistics and Data Analysis
Volume79
DOIs
Publication statusPublished - Nov 2014
Externally publishedYes

Fingerprint

Penalized Likelihood
Factor analysis
Oblique
Factor Analysis
Common factor
Lasso
Model
Penalization Method
Penalized Maximum Likelihood
Coordinate Descent
Entire Solution
EM Algorithm
Maximum likelihood
Penalty
Data analysis
Exceed
Monte Carlo Simulation
Estimate

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

Estimation of an oblique structure via penalized likelihood factor analysis. / Hirose, Kei; Yamamoto, Michio.

In: Computational Statistics and Data Analysis, Vol. 79, 11.2014, p. 120-132.

Research output: Contribution to journalArticle

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