Abstract
Conditional Gibbs partitions naturally arise in Bayesian nonparametric analysis of species sampling problems under almost surely discrete priors inducing infinite exchangeable partitions with distribution in Gibbs product form. In this setting interest relies on posterior predictive inference on some characteristics of a population of species, given an initial sample of observations. Here we focus on the subclass of Poisson-Kingman partitions driven by the Stable subordinator, and, relying on the unconditional theory of exchangeable Gibbs partitions, derive some additional results for the posterior partition, the conditional α diversity and a Stirling’s approximation of the Gibbs weights.
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The author is partially supported by grant PRIN MIUR:2008CEFF37.
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Cerquetti, A. (2013). Some Contributions to the Theory of Conditional Gibbs Partitions. In: Grigoletto, M., Lisi, F., Petrone, S. (eds) Complex Models and Computational Methods in Statistics. Contributions to Statistics. Springer, Milano. https://doi.org/10.1007/978-88-470-2871-5_7
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