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Robust Zero-Inflated Model/Evidence
Method evidence record

Robust Zero-Inflated Model

The robust zero-inflated model extends standard zero-inflated count regression — which handles excess zeros via a mixture of a point mass at zero and a count distribution — by replacing or supplementing classical maximum likelihood with robust estimation techniques (M-estimators, sandwich standard errors) that protect against the distorting influence of outlying observations.

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Source record

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

Robust Zero-Inflated Count Regression Model
Taxonomic method record · regression-model / statistics
  • Zeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25. · DOI 10.18637/jss.v027.i08
  • Cantoni, E., & Ronchetti, E. (2001). Robust inference for generalized linear models. Journal of the American Statistical Association, 96(455), 1022–1030. · DOI 10.1198/016214501753209004
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Related methods

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Taxonomic bucketRobust Generalized linear modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Negative Binomial Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Poisson Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketZero-inflated modelmachine-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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