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CC BY V4.0, Open Access
Preprint
A Gibbs Sampling Scheme for a Generalised Poisson-Kingman Class
ArXiv.org
Cornell University
2024
Abstract
A Bayesian nonparametric method of James, Lijoi \& Prunster (2009) used to predict future values of observations from normalized random measures with independent increments is modified to a class of models based on negative binomial processes for which the increments are not independent, but are independent conditional on an underlying gamma variable. Like in James et al., the new algorithm is formulated in terms of two variables, one a function of the past observations, and the other an updating by means of a new observation. We outline an application of the procedure to population genetics, for the construction of realisations of genealogical trees and coalescents from samples of alleles.
Details
- Title
- A Gibbs Sampling Scheme for a Generalised Poisson-Kingman Class
- Authors/Creators
- Robert C GriffithsRoss A MallerSoudabeh Shemehsavar
- Publication Details
- ArXiv.org
- Publisher
- Cornell University
- Identifiers
- 991005639770307891
- Murdoch Affiliation
- College of Science, Technology, Engineering and Mathematics
- Language
- English
- Resource Type
- Preprint
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