เปรียบเทียบวิธี

	Holt-Winters Triple Exponential Smoothing	แบบจำลอง ARIMA (Autoregressive Integrated Moving Average)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1960	2015
ผู้ริเริ่ม	Charles C. Holt and Peter R. Winters	Box & Jenkins (Box-Jenkins methodology)
ประเภท	Exponential smoothing forecasting model	Univariate time-series model
แหล่งต้นตำรับ	Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342.	Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
ชื่อเรียกอื่น	triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
ที่เกี่ยวข้อง	4	5
สรุป	Holt-Winters triple exponential smoothing is a forecasting model that extends Holt's double smoothing by adding a seasonal component, introduced by Peter Winters in 1960 building on Charles Holt's work. It tracks three evolving quantities — level, trend, and season — and combines them to forecast a continuous time series.	ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).