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A bivariate Dirichlet process

Author

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  • Walker, Stephen
  • Muliere, Pietro

Abstract

This paper introduces a bivariate Dirichlet process for modelling a partially exchangeable sequence of observables. The proposed model would be relevant when two distributions are unknown but are thought to be close to each other. For two random distributions with the same marginals, the belief in the degree of closeness is expressed through the correlation between masses assigned to equal sets.

Suggested Citation

  • Walker, Stephen & Muliere, Pietro, 2003. "A bivariate Dirichlet process," Statistics & Probability Letters, Elsevier, vol. 64(1), pages 1-7, August.
    • Handle: RePEc:eee:stapro:v:64:y:2003:i:1:p:1-7
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    Citations

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    Cited by:

    1. Muliere, Pietro & Secchi, Piercesare & Walker, Stephen, 2005. "Partially exchangeable processes indexed by the vertices of a k-tree constructed via reinforcement," Stochastic Processes and their Applications, Elsevier, vol. 115(4), pages 661-677, April.
    2. Trippa, Lorenzo & Muliere, Pietro, 2009. "Bayesian nonparametric binary regression via random tessellations," Statistics & Probability Letters, Elsevier, vol. 79(21), pages 2273-2280, November.
    3. Igor Prünster & Matteo Ruggiero, 2011. "A Bayesian nonparametric approach to modeling market share dynamics," Carlo Alberto Notebooks 217, Collegio Carlo Alberto.
    4. Rebecca Graziani & Michele Guindani & Peter F. Thall, 2015. "Bayesian nonparametric estimation of targeted agent effects on biomarker change to predict clinical outcome," Biometrics, The International Biometric Society, vol. 71(1), pages 188-197, March.
    5. Ilenia Epifani & Antonio Lijoi, 2009. "Nonparametric Priors for Vectors of Survival Functions," Quaderni di Dipartimento 098, University of Pavia, Department of Economics and Quantitative Methods.

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