Modeling overdispersion with the normalized tempered stable distribution
Kolossiatis, Michalis, Griffin, Jim E. and Steel, Mark F. J.. (2011) Modeling overdispersion with the normalized tempered stable distribution. Computational Statistics & Data Analysis, Vol.55 (No.7). pp. 2288-2301. ISSN 0167-9473Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.csda.2011.01.016
A multivariate distribution which generalizes the Dirichlet distribution is introduced and its use for modeling overdispersion in count data is discussed. The distribution is constructed by normalizing a vector of independent tempered stable random variables. General formulae for all moments and cross-moments of the distribution are derived and they are found to have similar forms to those for the Dirichlet distribution. The univariate version of the distribution can be used as a mixing distribution for the success probability of a binomial distribution to define an alternative to the well-studied beta-binomial distribution. Examples of fitting this model to simulated and real data are presented.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics|
|Divisions:||Faculty of Science > Statistics|
|Library of Congress Subject Headings (LCSH):||Multivariate analysis, Distribution (Probability theory)|
|Journal or Publication Title:||Computational Statistics & Data Analysis|
|Publisher:||Elsevier Science Ltd|
|Official Date:||1 July 2011|
|Page Range:||pp. 2288-2301|
|Access rights to Published version:||Restricted or Subscription Access|
|Version or Related Resource:||Kolossiatis, M., Griffin, J.E. and Steel, M.F.J. (2011). Modelling overdispersion with the normalized tempered stable distribution. [Coventry] : University of Warwick. Centre for Research in Statistical Methodology. (Working papers, no.10-01). http://wrap.warwick.ac.uk/id/eprint/35065|
Aeschbacher, H.U., Vuataz, L., Sotek, J., Stalder, R., 1977. The use of the beta-binomial distribution in dominant-lethal testing for weak mutagenic activity
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