A Selective Overview of Semiparametric Mixture of Regression Models
Finite mixture of regression models have been popularly used in many applications. In this article, we did a systematic review of newly developed semiparametric mixture of regression models. Recent developments and some open questions are also discussed.
Xiang’s research is supported by Zhejiang Provincial NSF of China [grant no. LQ16A010002] and NSF of China [grant no. 11601477]. Yao’s research is supported by NSF [grant no. DMS-1461677] and Department of Energy with the award DE-EE0007328.
- Frühwirth-Schnatter, S. (2006). Finite mixture and Markov switching models. New York: Springer.Google Scholar
- Pena, D., Rodríguez, J., & Tiao, G. C. (2003). Identifying mixtures of regression equations by the SAR procedure. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian statistics (Vol. 7, pp. 327–348). Oxford: Clarendon Press.Google Scholar
- Xiang, S., & Yao, W. (2017). Semiparametric mixtures of regressions with single-index for model based clustering. arXiv:1708.04142v1.Google Scholar