เปรียบเทียบวิธี

	แบบจำลอง Nonlinear SARIMA	แบบจำลอง ARIMA (Autoregressive Integrated Moving Average)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1990–2000	1970
ผู้ริเริ่ม	Tong (1990) for threshold nonlinear extensions; Franses & van Dijk (2000) for empirical finance applications	George Box and Gwilym Jenkins
ประเภท	Nonlinear time series model	Time series forecasting model
แหล่งต้นตำรับ	Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 978-0198523000	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
ชื่อเรียกอื่น	NL-SARIMA, nonlinear seasonal ARIMA, threshold SARIMA, smooth transition SARIMA	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
ที่เกี่ยวข้อง	3	6
สรุป	The Nonlinear SARIMA model extends the classical Seasonal ARIMA framework by replacing the linear conditional mean function with a nonlinear specification — such as threshold switching or smooth transition — while retaining seasonal differencing and lag structure. It is used when seasonal time series exhibit regime-dependent dynamics, asymmetric adjustment, or other nonlinear patterns that a linear model cannot capture.	The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.