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Asymptotics for the number of blocks in a conditional Ewens-Pitman sampling model

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	Asymptotics for the number of blocks in a conditional Ewens-Pitman sampling model
2.	Creator	Author's name, affiliation, country	Stefano Favaro; University of Torino and Collegio Carlo Alberto; Italy
2.	Creator	Author's name, affiliation, country	Shui Feng; McMaster University; Canada
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	Bayesian nonparametrics; Dirichlet process; Ewens-Pitman sampling model; exchangeable random partition; fluctuation limit; large deviations; two parameter Poisson-Dirichlet process
3.	Subject	Subject classification	60F10; 92D10
4.	Description	Abstract	The study of random partitions has been an active research area in probability over the last twenty years. A quantity that has attracted a lot of attention is the number of blocks in the random partition. Depending on the area of applications this quantity could represent the number of species in a sample from a population of individuals or he number of cycles in a random permutation, etc. In the context of Bayesian nonparametric inference such a quantity is associated with the exchangeable random partition induced by sampling from certain prior models, for instance the Dirichlet process and the two parameter Poisson-Dirichlet process. In this paper we generalize some existing asymptotic results from this prior setting to the so-called posterior, or conditional, setting. Specifically, given an initial sample from a two parameter Poisson-Dirichlet process, we establish conditional fluctuation limits and conditional large deviation principles for the number of blocks generated by a large additional sample.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)
7.	Date	(YYYY-MM-DD)	2014-02-18
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ejp.ejpecp.org/article/view/2881
10.	Identifier	Digital Object Identifier	10.1214/EJP.v19-2881
11.	Source	Journal/conference title; vol., no. (year)	Electronic Journal of Probability; Vol 19
12.	Language	English=en	en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
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