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Robust Factor Analysis/Evidence
Method evidence record

Robust Factor Analysis

Robust Factor Analysis recovers the latent factor structure of multivariate continuous data while resisting the distorting pull of outliers. Introduced by Pison, Rousseeuw, Filzmoser and Croux (2003), it replaces the classical sample covariance with a robust estimator such as the Minimum Covariance Determinant (MCD) or an S-estimator before extracting factors.

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

Robust Factor Analysis
Taxonomic method record · regression-model / statistics
  • Pison, G., Rousseeuw, P. J., Filzmoser, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84(1), 145-172. · DOI 10.1016/S0047-259X(02)00007-6
  • Hubert, M., Rousseeuw, P. J., & Vanden Branden, K. (2005). ROBPCA: A new approach to robust principal component analysis. Technometrics, 47(1), 64-79. · DOI 10.1198/004017004000000563
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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.

See alsoFactor Analysismachine-suggested · Relational suggestion, not evidence.Same method familyInfluence Diagnosticsmachine-suggested · Relational suggestion, not evidence.See alsoPrincipal Component Analysismachine-suggested · Relational suggestion, not evidence.Same method familyRobust Covariance (MCD)machine-suggested · Relational suggestion, not evidence.Same method familyRobust PCAmachine-suggested · Relational suggestion, not evidence.

Evidence status

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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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