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Bayesian model averaging sliced inverse regression

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  • Power, Michael Declan
  • Dong, Yuexiao

Abstract

As a popular sufficient dimension reduction method, sliced inverse regression (SIR) (Li, 1991) involves all the predictors. We propose Bayesian model averaging SIR when the central space only involves a subset of the predictors.

Suggested Citation

  • Power, Michael Declan & Dong, Yuexiao, 2021. "Bayesian model averaging sliced inverse regression," Statistics & Probability Letters, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:stapro:v:174:y:2021:i:c:s0167715221000651
    DOI: 10.1016/j.spl.2021.109103
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    References listed on IDEAS

    as
    1. Lexin Li, 2007. "Sparse sufficient dimension reduction," Biometrika, Biometrika Trust, vol. 94(3), pages 603-613.
    2. P. J. Brown & M. Vannucci & T. Fearn, 1998. "Multivariate Bayesian variable selection and prediction," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(3), pages 627-641.
    3. Fang, Fang & Yu, Zhou, 2020. "Model averaging assisted sufficient dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    4. Harrison, David Jr. & Rubinfeld, Daniel L., 1978. "Hedonic housing prices and the demand for clean air," Journal of Environmental Economics and Management, Elsevier, vol. 5(1), pages 81-102, March.
    5. Ming Yuan & Yi Lin, 2006. "Model selection and estimation in regression with grouped variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 49-67, February.
    Full references (including those not matched with items on IDEAS)

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