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Robust MA-modell (Robust Moving Average Model)×Moving Average (MA) Model×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1979–20091970
UpphovspersonDenby & Martin (1979); Muler, Pena & Yohai (2009)Box and Jenkins
TypRobust time series modelLinear time series model
UrsprungskällaDenby, L., & Martin, R. D. (1979). Robust estimation of the first-order autoregressive parameter. Journal of the American Statistical Association, 74(365), 140–146. DOI ↗Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Aliasrobust MA, robust moving average, M-estimation MA, bounded-influence MAMA model, MA(q) process, moving-average process, Box-Jenkins MA
Närliggande65
SammanfattningThe Robust MA model applies robust estimation — typically M-estimation or bounded-influence methods — to the Moving Average time series model. By replacing the ordinary least squares loss with a bounded loss function, it produces parameter estimates that are far less sensitive to outliers, additive noise spikes, or heavy-tailed error distributions than the classical Gaussian MA.The Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods.
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ScholarGateJämför metoder: Robust MA model · Moving Average Model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare