เปรียบเทียบวิธี

	โมเดล Robust SARIMA	X-13ARIMA-SEATS การปรับฤดูกาล
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Process / pipeline
ปีกำเนิด	1979–2009	1998
ผู้ริเริ่ม	Muler, Peña & Yohai (robust ARMA); earlier foundation by Denby & Martin (1979)	U.S. Census Bureau; Findley et al.
ประเภท	Robust time-series model	Non-parametric / model-based hybrid
แหล่งต้นตำรับ	Muler, N., Peña, D., & Yohai, V. J. (2009). Robust estimation for ARMA models. The Annals of Statistics, 37(2), 816–840.	Findley, D. F., Monsell, B. C., Bell, W. R., Otto, M. C., & Chen, B.-C. (1998). New capabilities and methods of the X-12-ARIMA seasonal adjustment program. Journal of Business & Economic Statistics, 16(2), 127–152.
ชื่อเรียกอื่น	robust SARIMA, outlier-resistant SARIMA, robust seasonal ARIMA, M-estimator SARIMA	X-13ARIMA-SEATS, X-12-ARIMA, Census X-13, Mevsimsel Düzeltme X-13
ที่เกี่ยวข้อง	4	3
สรุป	Robust SARIMA extends the classical Seasonal ARIMA framework by replacing the standard least-squares criterion with a robust loss function — such as an M-estimator — so that outliers and heavy-tailed innovations in seasonal time series cannot distort parameter estimates or invalidate forecasts.	X-13ARIMA-SEATS is the standard seasonal adjustment program produced by the U.S. Census Bureau, combining RegARIMA pre-adjustment with either the classical X-11 filter or the model-based SEATS signal-extraction algorithm. It is the official tool used by national statistical agencies worldwide — including Eurostat and the U.S. Bureau of Labor Statistics — to remove recurring calendar and seasonal patterns from monthly or quarterly economic time series such as GDP, employment, and retail sales.