Method evidence record
Zero-Inflated Negative Binomial Regression
Zero-Inflated Negative Binomial regression is a count model, introduced by Greene (1994), that handles count data showing both an excess of zeros and overdispersion. It combines a binary inflation process that generates structural zeros with a negative binomial count process, making it one of the most widely used distributions for real-world count data.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
Zero-Inflated Negative Binomial (ZINB) Regression
Taxonomic method record · regression-model / statistics
Open full method Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
No curated claims yet
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.