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Regression modelEconometrics / time series

Robust ARIMA mudel

Robust ARIMA laiendab klassikalist ARIMA raamistikku, et tuvastada ja parandada және mõju mõju ja struktuuriliste murrangute mõju hindamise ajal. Koos anomaalsete vaatluste tuvastamise ja mudeliparameetrite uuesti hindamisega toodab see koefitsientide hinnanguid ja prognoose, mis on vähem moonutatud isoleeritud šokkide või andmevigade poolt kui standardne ARIMA.

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Allikad

  1. Tsay, R. S. (1986). Time series model specification in the presence of outliers. Journal of the American Statistical Association, 81(393), 132–141. DOI: 10.1080/01621459.1986.10478250
  2. Chen, C., & Liu, L.-M. (1993). Joint estimation of model parameters and outlier effects in time series. Journal of the American Statistical Association, 88(421), 284–297. DOI: 10.2307/2290724

Kuidas sellele lehele viidata

ScholarGate. (2026, June 3). Robust Autoregressive Integrated Moving Average Model. ScholarGate. https://scholargate.app/et/econometrics/robust-arima-model

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Sellele viitavad

ScholarGateRobust ARIMA model (Robust Autoregressive Integrated Moving Average Model). Loetud 2026-06-15 aadressilt https://scholargate.app/et/econometrics/robust-arima-model · Andmestik: https://doi.org/10.5281/zenodo.20539026