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Robust ARIMA model/Evidence
Method evidence record

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.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Robust Autoregressive Integrated Moving Average Model
Taxonomic method record · 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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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketARIMA modelmachine-suggested · Relational suggestion, not evidence.Same method familyQuantile Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSARIMA modelmachine-suggested · Relational suggestion, not evidence.Same method familyState Space Modelmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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