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On a Low-Rank Matrix Single-Index Model

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  • The Tien Mai

    (Department of Mathematical Sciences, Norwegian University of Science and Technology, 7034 Trondheim, Norway)

Abstract

In this paper, we conduct a theoretical examination of a low-rank matrix single-index model. This model has recently been introduced in the field of biostatistics, but its theoretical properties for jointly estimating the link function and the coefficient matrix have not yet been fully explored. In this paper, we make use of the PAC-Bayesian bounds technique to provide a thorough theoretical understanding of the joint estimation of the link function and the coefficient matrix. This allows us to gain a deeper insight into the properties of this model and its potential applications in different fields.

Suggested Citation

  • The Tien Mai, 2023. "On a Low-Rank Matrix Single-Index Model," Mathematics, MDPI, vol. 11(9), pages 1-16, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2065-:d:1133872
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    References listed on IDEAS

    as
    1. Efang Kong & Yingcun Xia, 2007. "Variable selection for the single‐index model," Biometrika, Biometrika Trust, vol. 94(1), pages 217-229.
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