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Rregullimi Sezonal X-13ARIMA-SEATS×STL Decomposition: Seasonal-Trend Decomposition using Loess×
FushaEkonometriEkonometri
FamiljaProcess / pipelineProcess / pipeline
Viti i origjinës19981990
KrijuesiU.S. Census Bureau; Findley et al.Cleveland, Cleveland, McRae & Terpenning
LlojiNon-parametric / model-based hybridnonparametric iterative smoother
Burimi themeluesFindley, 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. DOI ↗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. link ↗
Emërtime të tjeraX-13ARIMA-SEATS, X-12-ARIMA, Census X-13, Mevsimsel Düzeltme X-13Seasonal-Trend Decomposition using Loess, STL filtering, Loess-based seasonal decomposition, Mevsimsel-Trend Ayrıştırma (STL)
Të lidhura33
PërmbledhjaX-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.
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ScholarGateKrahasoni metodat: X-13ARIMA-SEATS · STL Decomposition. Marrë më 2026-06-19 nga https://scholargate.app/sq/compare