APA (7th ed.) Citation

Yu, L., Zhou, L., Tan, L., Jiang, H., Wang, Y., Wei, S., & Nie, S. (2014). Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China. Public Library of Science (PLoS).

Chicago Style (17th ed.) Citation

Yu, Lijing, Lingling Zhou, Li Tan, Hongbo Jiang, Ying Wang, Sheng Wei, and Shaofa Nie. Application of a New Hybrid Model with Seasonal Auto-regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China. Public Library of Science (PLoS), 2014.

MLA (8th ed.) Citation

Yu, Lijing, et al. Application of a New Hybrid Model with Seasonal Auto-regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China. Public Library of Science (PLoS), 2014.