COMPoissonReg: Conway-Maxwell Poisson Regression for Count Data

A statistical package for fitting Conway-Maxwell Poisson (COM-Poisson or CMP) regression models to count data, as described by Sellers and Shmueli (2010). The package provides functions for model estimation, dispersion testing, and diagnostics, and also supports zero-inflated CMP regression (Sellers and Raim, 2016). It was authored by Kimberly Sellers, Thomas Lotze, and Andrew Raim.

Use Cases

• Modeling over- or under-dispersed count data based on the COM-Poisson distribution mentioned in the description.
• Performing dispersion testing for count regression models based on the diagnostic functions provided.
• Fitting zero-inflated count models based on the supported zero-inflated CMP regression functionality.

Strengths

• Implements a specialized regression model (COM-Poisson) for count data, providing an alternative to standard Poisson regression.
• Includes support for zero-inflated model variants, expanding its applicability to common data scenarios.
• Provides diagnostic functions for model assessment, as mentioned in the description.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale applications.
• Last update date is unknown; freshness unverified.

Provenance

Source

paperswithcode

Collection Method

Software package for statistical modeling.

Time Range

null

Freshness

Last updated date is unknown.

Geography

null