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Robust Multidimensional Scaling/Evidence
Method evidence record

Robust Multidimensional Scaling

Robust multidimensional scaling recovers a low-dimensional spatial map from a matrix of pairwise dissimilarities while resisting distortion caused by outlying or erroneous proximity values. By replacing squared-error loss with a robust loss function or down-weighting suspect pairs, it produces a configuration that faithfully represents the bulk of the data even when some distances are grossly atypical.

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Source record

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

Robust Multidimensional Scaling
Taxonomic method record · latent-structure / statistics
  • Hubert, L., Arabie, P. & Meulman, J. (2002). Linear unidimensional scaling in the L2-norm: Basic optimization methods using SMACOF. Journal of Classification, 19(2), 303–327. · URL
  • Buja, A., Swayne, D. F., Littman, M. L., Dean, N., Hofmann, H. & Chen, L. (2008). Data visualization with multidimensional scaling. Journal of Computational and Graphical Statistics, 17(2), 444–472. · DOI 10.1198/106186008X318440
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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 bucketMultidimensional Scalingmachine-suggested · Relational suggestion, not evidence.Used in the same domainRobust Cluster Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Correspondence Analysismachine-suggested · Relational suggestion, not evidence.Same method familyRobust Exploratory Factor Analysismachine-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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