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March 2007 On the multimodality of random probability measures
George Kokolakis, George Kouvaras
Bayesian Anal. 2(1): 213-219 (March 2007). DOI: 10.1214/07-BA208


Nonparametric methods for density estimation are examined here. Within a Bayesian setting the construction of an absolutely continuous random probability measure is often required for nonparametric statistical analysis. To achieve this we propose a "partial convexification" procedure of a process, such as the Dirichlet, resulting in a multimodal distribution function with a finite expected number of modes. In agreement with convexity theory results, it is shown that the derived random probability measure admits a density with respect to Lebesgue measure.


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George Kokolakis. George Kouvaras. "On the multimodality of random probability measures." Bayesian Anal. 2 (1) 213 - 219, March 2007.


Published: March 2007
First available in Project Euclid: 22 June 2012

zbMATH: 1331.62199
MathSciNet: MR2289928
Digital Object Identifier: 10.1214/07-BA208

Primary: Database Expansion Item

Keywords: convexity , Dirichlet process , multimodal distribution functions , Polya trees , random probability measures

Rights: Copyright © 2007 International Society for Bayesian Analysis


Vol.2 • No. 1 • March 2007
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