方法证据记录
Robust ARIMA model
Robust ARIMA extends the classical ARIMA framework to detect and correct the influence of outliers and structural breaks during estimation. By jointly identifying anomalous observations and re-estimating model parameters, it produces coefficient estimates and forecasts that are far less distorted by isolated shocks or data errors than standard ARIMA.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Autoregressive Integrated Moving Average Model
分类方法记录 · regression-model / econometrics
- 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
- 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
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