EM Algorithm Amendment of Zero-and-one Inflated Binomial Mixture Regression Model

doi:10.3969/j.issn.1006-2475.2018.03.012

Abstract

Abstract: This paper proposes a zero-and-one inflated regression model with “heterogeneity”. Since standard EM algorithm will make the parameter estimates converge to local optimum, this paper introduces the MCEM algorithm to address this shortcoming, then the estimation of parameter is setted up for the zero-and-one inflated binomial mixture regression model. Finally, the corresponding simulation is given to illustrate the proposed method.

Key words: zero-and-one inflation, mixture regression, acceleration of MCEM algorithm

CLC Number:

TP309.2

LYU Min-hong1, YAN Yi-rong2, WU Cheng-jing1. EM Algorithm Amendment of Zero-and-one Inflated Binomial Mixture Regression Model[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.03.012.

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