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Rotation to Sparse Loadings Using $$L^p$$ L p Losses and Related Inference Problems

Author

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  • Xinyi Liu

    (London School of Economics and Political Science)

  • Gabriel Wallin

    (London School of Economics and Political Science
    Umeå University)

  • Yunxiao Chen

    (London School of Economics and Political Science)

  • Irini Moustaki

    (London School of Economics and Political Science)

Abstract

Researchers have widely used exploratory factor analysis (EFA) to learn the latent structure underlying multivariate data. Rotation and regularised estimation are two classes of methods in EFA that they often use to find interpretable loading matrices. In this paper, we propose a new family of oblique rotations based on component-wise $$L^p$$ L p loss functions $$(0

Suggested Citation

  • Xinyi Liu & Gabriel Wallin & Yunxiao Chen & Irini Moustaki, 2023. "Rotation to Sparse Loadings Using $$L^p$$ L p Losses and Related Inference Problems," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 527-553, June.
    • Handle: RePEc:spr:psycho:v:88:y:2023:i:2:d:10.1007_s11336-023-09911-y
    DOI: 10.1007/s11336-023-09911-y
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    References listed on IDEAS

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