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Bayesian Robust Regression/Evidence
Method evidence record

Bayesian Robust Regression

Bayesian Robust Regression replaces the Gaussian error assumption of ordinary linear regression with a heavy-tailed distribution — most commonly the Student-t — and estimates all parameters in a Bayesian framework. The heavier tails give outliers less influence on the fitted line, yielding stable coefficient estimates and honest uncertainty intervals even when the data contain unusual observations.

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Source record

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

Bayesian Robust Regression
Taxonomic method record · regression-model / statistics
  • Geweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40. · DOI 10.1002/jae.3950080504
  • Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. · ISBN 978-1439840955
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

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

Taxonomic bucketBayesian Generalized Linear Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Multiple linear regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Quantile Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyOLS Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyQuantile Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Regressionmachine-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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