Сравнение на методи

	Сезонна корекция X-13ARIMA-SEATS	STL разлагане: Разлагане на сезонност и тренд чрез Loess
Област	Иконометрия	Иконометрия
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1998	1990
Създател	U.S. Census Bureau; Findley et al.	Cleveland, Cleveland, McRae & Terpenning
Тип	Non-parametric / model-based hybrid	nonparametric iterative smoother
Основополагащ източник	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.	Cleveland, R. B., Cleveland, W. S., McRae, J. E., & Terpenning, I. (1990). STL: A seasonal-trend decomposition procedure based on loess. Journal of Official Statistics, 6(1), 3–73.
Други названия	X-13ARIMA-SEATS, X-12-ARIMA, Census X-13, Mevsimsel Düzeltme X-13	Seasonal-Trend Decomposition using Loess, STL filtering, Loess-based seasonal decomposition, Mevsimsel-Trend Ayrıştırma (STL)
Свързани	3	3
Резюме	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.	STL Decomposition, introduced by Cleveland, Cleveland, McRae, and Terpenning (1990), is a nonparametric procedure that separates a time series into three additive components — trend, seasonal, and remainder — using iterative locally weighted regression (loess). Widely used in economics, meteorology, and data science, it handles time series of any periodicity and is robust to the presence of outliers, making it a highly flexible alternative to classical decomposition methods.