Generalized poisson models arising from Markov processes
We develop a family of distributions which allow for over- and underdispersion relative to the Poisson. This latter feature is particularly appealing since many existing methods only allow for overdispersion. These distributions arise from underlying continuous-time Markov processes in which event rates depend on how many events have already occurred. The results are illustrated with underdispersed count data from a polyspermy study and overdispersed data from the Canadian Sickness Survey.
Year of publication: |
1998
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Authors: | Bosch, Ronald J. ; Ryan, Louise M. |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 39.1998, 3, p. 205-212
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Publisher: |
Elsevier |
Keywords: | Birth process Overdispersion Underdispersion Differential equations |
Saved in:
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