Frontiers of Mathematics in China >

2020 , Vol. 15 >Issue 1: 141 - 154

DOI: https://doi.org/10.1007/s11464-020-0813-5

RESEARCH ARTICLE

Mixture network autoregressive model with application on students' successes

  • Weizhong TIAN , 1 ,
  • Fengrong WEI 2 ,
  • Thomas BROWN 1
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  • 1. Department of Mathematical Sciences, Eastern New Mexico University, Portales, NM 88130, USA
  • 2. Department of Mathematics, University of West Georgia, Carrollton, GA 30118, USA

Received date: 08 Nov 2018

Accepted date: 21 Dec 2019

Published date: 15 Feb 2020

Copyright

2020 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
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Abstract

We propose a mixture network regression model which considers both response variables and the node-specific random vector depend on the time. In order to estimate and compare the impacts of various connections on a response variable simultaneously, we extend it into p different types of connections. An ordinary least square estimators of the effects of different types of connections on a response variable is derived with its asymptotic property. Simulation studies demonstrate the effectiveness of our proposed method in the estimation of the mixture autoregressive model. In the end, a real data illustration on the students' GPA is discussed.

Key words： Network regression; multiple connections; heterogeneous; dynamic effects

Cite this article

Weizhong TIAN , Fengrong WEI , Thomas BROWN . Mixture network autoregressive model with application on students' successes[J]. Frontiers of Mathematics in China, 2020 , 15(1) : 141 -154 . DOI: 10.1007/s11464-020-0813-5

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