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jbowman
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The Conway-Maxwell-Poisson distribution (https://en.wikipedia.org/wiki/Conway%E2%80%93Maxwell%E2%80%93Poisson_distribution) has unbounded support (on the right) and can model both under- and over-dispersion (relative to the Poisson) seamlessly through the use of a single parameter. The Poisson is a special case. It can't handle any amount of underdispersion, though, and it is relatively computationally intensive. It is a member of the exponential family of distributions.

R packages exist for both estimation and regression:

https://cran.r-project.org/web/packages/CompGLM/CompGLM.pdf

https://cran.r-project.org/web/packages/COMPoissonReg/COMPoissonReg.pdf

https://cran.r-project.org/web/packages/compoisson/compoisson.pdf

although I haven't used them so cannot make any helpful comments about their relative quality / usefulness!

The Conway-Maxwell-Poisson distribution (https://en.wikipedia.org/wiki/Conway%E2%80%93Maxwell%E2%80%93Poisson_distribution) has unbounded support and can model both under- and over-dispersion (relative to the Poisson) seamlessly through the use of a single parameter. The Poisson is a special case. It can't handle any amount of underdispersion, though, and it is relatively computationally intensive. It is a member of the exponential family of distributions.

R packages exist for both estimation and regression:

https://cran.r-project.org/web/packages/CompGLM/CompGLM.pdf

https://cran.r-project.org/web/packages/COMPoissonReg/COMPoissonReg.pdf

https://cran.r-project.org/web/packages/compoisson/compoisson.pdf

although I haven't used them so cannot make any helpful comments about their relative quality / usefulness!

The Conway-Maxwell-Poisson distribution (https://en.wikipedia.org/wiki/Conway%E2%80%93Maxwell%E2%80%93Poisson_distribution) has unbounded support (on the right) and can model both under- and over-dispersion (relative to the Poisson) seamlessly through the use of a single parameter. The Poisson is a special case. It can't handle any amount of underdispersion, though, and it is relatively computationally intensive. It is a member of the exponential family of distributions.

R packages exist for both estimation and regression:

https://cran.r-project.org/web/packages/CompGLM/CompGLM.pdf

https://cran.r-project.org/web/packages/COMPoissonReg/COMPoissonReg.pdf

https://cran.r-project.org/web/packages/compoisson/compoisson.pdf

although I haven't used them so cannot make any helpful comments about their relative quality / usefulness!

Source Link
jbowman
  • 42.2k
  • 8
  • 79
  • 142

The Conway-Maxwell-Poisson distribution (https://en.wikipedia.org/wiki/Conway%E2%80%93Maxwell%E2%80%93Poisson_distribution) has unbounded support and can model both under- and over-dispersion (relative to the Poisson) seamlessly through the use of a single parameter. The Poisson is a special case. It can't handle any amount of underdispersion, though, and it is relatively computationally intensive. It is a member of the exponential family of distributions.

R packages exist for both estimation and regression:

https://cran.r-project.org/web/packages/CompGLM/CompGLM.pdf

https://cran.r-project.org/web/packages/COMPoissonReg/COMPoissonReg.pdf

https://cran.r-project.org/web/packages/compoisson/compoisson.pdf

although I haven't used them so cannot make any helpful comments about their relative quality / usefulness!