Frontiers of Mathematics in China >
Mixture network autoregressive model with application on students' successes
Received date: 08 Nov 2018
Accepted date: 21 Dec 2019
Published date: 15 Feb 2020
Copyright
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
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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