Review Articles

Comment on ‘Review of sparse sufficient dimension reduction’

Michael Declan Power ,

Department of Statistical Science, Temple University, Philadelphia, PA, USA

Yuexiao Dong

Department of Statistical Science, Temple University, Philadelphia, PA, USA

Pages 149-150 | Received 18 Sep. 2020, Accepted 23 Sep. 2020, Published online: 13 Oct. 2020,
  • Abstract
  • Full Article
  • References
  • Citations


  1. Brown, P. J., Vannucci, M., & Fearn, T. (1998). Multivariate Bayesian variable selection and prediction. Journal of the Royal Statistical Society: Series B (Statistical Methodology)60(3), 627–641. doi: 10.1111/1467-9868.00144 [Crossref][Web of Science ®], [Google Scholar]
  2. Fang, F., & Yu, Z. (2020). Model averaging assisted sufficient dimension reduction. Computational Statistics and Data Analysis152 [Crossref][Web of Science ®], [Google Scholar]
  3. Hansen, B. E. (2007). Least squares model averaging. Econometrica75(4), 1175–1189. doi: 10.1111/j.1468-0262.2007.00785.x [Crossref][Web of Science ®], [Google Scholar]
  4. Li, K. (1991). Sliced inverse regression for dimension reduction. Journal of the American Statistical Association86(414), 316–327. [Taylor & Francis Online][Web of Science ®], [Google Scholar]
  5. Power, M. D., & Dong, Y. (2020). Bayesian model averaging sufficient dimension reduction. Statistics and Probability Letters. Submitted. [Google Scholar]
  6. Raftery, A. E., Madigan, D., & Hoeting, J. A. (1997). Bayesian model averaging for linear regression models. Journal of the American Statistical Association92(437), 179–191. [Taylor & Francis Online][Web of Science ®], [Google Scholar]
  7. Reich, B. J., Bondell, H. D., & Li, L. (2011). Sufficient dimension reduction via Bayesian mixture modeling. Biometrics67(3), 886–895. doi: 10.1111/j.1541-0420.2010.01501.x [Crossref][Web of Science ®], [Google Scholar]
  8. Tan, K., Shi, L., & Yu, Z. (2020). Sparse SIR: optimal rates and adaptive estimation. The Annals of Statistics48(1), 64–85. [Crossref][Web of Science ®], [Google Scholar]
  9. Yu, Z., Dong, Y., & Shao, J. (2016). On marginal sliced inverse regression for ultrahigh dimensional model-free feature selection. The Annals of Statistics44(6), 2594–2623. [Crossref][Web of Science ®], [Google Scholar]