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Mixture network autoregressive model with application on students’successes

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摘要 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.
出处 《Frontiers of Mathematics in China》 SCIE CSCD 2020年第1期141-154,共14页 中国高等学校学术文摘·数学(英文)
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