Berti, Patrizia and Crimaldi, Irene and Pratelli, Luca and Rigo, Pietro Central Limit Theorems for an Indian Buffet Model with Random Weights. The Annals of Applied Probability, 25 (2). pp. 523547. ISSN 10505164 (2015)
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Abstract
The threeparameter Indian buffet process is generalized. The possibly different role played by customers is taken into account by suitable (random) weights. Various limit theorems are also proved for such generalized Indian buffet process. Let L_n be the number of dishes experimented by the first n customers, and let {\bar K}_n=(1/n)\sum_{i=1}^n K_i where K_i is the number of dishes tried by customer i. The asymptotic distributions of L_n and {\bar K}_n, suitably centered and scaled, are obtained. The convergence turns out to be stable (and not only in distribution). As a particular case, the results apply to the standard (i.e., non generalized) Indian buffet process.
Item Type:  Article 

Identification Number:  10.1214/14AAP1002 
Uncontrolled Keywords:  Bayesian nonparametrics, Central limit theorem, Conditional identity in distribution, Indian buffet process, Random measure, Random reinforcement, Stable convergence 
Subjects:  H Social Sciences > HA Statistics Q Science > QA Mathematics 
Research Area:  Economics and Institutional Change 
Depositing User:  Irene Crimaldi 
Date Deposited:  23 Feb 2015 08:34 
Last Modified:  23 Feb 2015 08:34 
URI:  http://eprints.imtlucca.it/id/eprint/2612 
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Central Limit Theorems for an Indian Buffet Model with Random Weights. (deposited 16 Apr 2013 14:59)

Central Limit Theorems for an Indian Buffet Model with Random Weights. (deposited 04 Feb 2014 08:35)
 Central Limit Theorems for an Indian Buffet Model with Random Weights. (deposited 23 Feb 2015 08:34) [Currently Displayed]

Central Limit Theorems for an Indian Buffet Model with Random Weights. (deposited 04 Feb 2014 08:35)
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