পদ্ধতির তুলনা করুন

	Holt-Winters Triple Exponential Smoothing	ARIMA (Autoregressive Integrated Moving Average) মডেল
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1960	2015
প্রবর্তক	Charles C. Holt and Peter R. Winters	Box & Jenkins (Box-Jenkins methodology)
ধরন	Exponential smoothing forecasting model	Univariate time-series model
মৌলিক উৎস	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
অপর নাম	triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
সম্পর্কিত	4	5
সারসংক্ষেপ	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).