DETECTING MULTIVARIATE SERIES DATA WITH TRANSFER FUNCTION ARIMAX FOR TEACHER DEMAND

淡江大學機構典藏 > 教育學院 > 教育政策與領導研究所 > 期刊論文 > Item 987654321/118156

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题名:	DETECTING MULTIVARIATE SERIES DATA WITH TRANSFER FUNCTION ARIMAX FOR TEACHER DEMAND
作者:	Wen-Ching Chou;Ko Lin Lai;Dian-Fu Chang
关键词:	ARIMA;ARIMAX;Cross-correlation function;Multivariate time series;Transfer function;Teacher demand
日期:	2020-02
上传时间:	2020-03-05 12:10:21 (UTC+8)
出版者:	ICIC International
摘要:	The universal ARIMA model did not fit two series concurrently. For example, the series of teacher demand is a case with multiple factors concurrently in its development process. Previous literature assumed that teacher demand can be forecasted independently through the model ARIMA (autoregressive integrated moving average). In this paper, we applied multivariate ARIMA mode, called ARIMAX, for determining the demand of teachers with the series data of students. We selected the series of data as an example from the Ministry of Education, Taiwan. The cross correlation function and transfer function have been applied to build the fittest ARIMAX model. The ARIMAX analyses indicate that predicting the number of teachers with number of students is better than that only using the universal series data of teacher demand. The implication of these findings may provide an optimal research design for determining the demand of teachers under the changing number of students in elementary schools.
關聯:	ICIC Express Letters Part B: Applications 11(2), p.129-136
DOI:	10.24507/icicelb.11.02.129
显示于类别:	[教育政策與領導研究所] 期刊論文

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