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  • Search: subject:"Polynomially and exponentially tilted random variables"
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Year of publication
Subject
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Asymptotics 3 Bayesian Nonparametrics 3 Completely random measures 3 Normalized generalized gamma process 3 Polynomially and exponentially tilted random variables 3 Species sampling models 3 Bayes-Statistik 1 Bayesian inference 1 Estimation theory 1 Nichtparametrisches Verfahren 1 Nonparametric statistics 1 Probability theory 1 Random variable 1 Sampling 1 Schätztheorie 1 Statistical theory 1 Statistische Methodenlehre 1 Stichprobenerhebung 1 Stochastic process 1 Stochastischer Prozess 1 Two parameter Poisson Dirichlet process 1 Two parameter Poisson–Dirichlet process 1 Two parameter Poisson–Dirichlet process 1 Wahrscheinlichkeitsrechnung 1 Zufallsvariable 1 s diversity 1 s–diversity 1 s–diversity 1
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Online availability
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Free 3
Type of publication
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Book / Working Paper 3
Type of publication (narrower categories)
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Graue Literatur 1 Non-commercial literature 1 Working Paper 1
Language
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English 3
Author
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Favaro, Stefano 3 Lijoi, Antonio 3 Prunster, Igor 2 Prünster, Igor 1
Institution
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Dipartimento di Scienze Economiche e Aziendali, Università degli Studi di Pavia 1
Published in...
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Quaderni di Dipartimento 2 Quaderni del Dipartimento 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
Cover Image
Asymptotics for a Bayesian nonparametric estimator of species richness
Favaro, Stefano; Lijoi, Antonio; Prunster, Igor - 2011
In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on the clustering of the data. Recently it has been shown that they can also be exploited in species sampling...
Persistent link: https://www.econbiz.de/10010335257
Saved in:
Cover Image
Asymptotics for a Bayesian nonparametric estimator of species richness
Favaro, Stefano; Lijoi, Antonio; Prunster, Igor - Dipartimento di Scienze Economiche e Aziendali, … - 2011
In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on the clustering of the data. Recently it has been shown that they can also be exploited in species sampling...
Persistent link: https://www.econbiz.de/10009651024
Saved in:
Cover Image
Asymptotics for a Bayesian nonparametric estimator of species richness
Favaro, Stefano; Lijoi, Antonio; Prünster, Igor - 2011
In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on the clustering of the data. Recently it has been shown that they can also be exploited in species sampling...
Persistent link: https://www.econbiz.de/10010343850
Saved in:
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