On Bayesian nonparametric modelling of two correlated distributions

Statistics and Computing

Volumn 23, Issue 1, 2013, Pages 1-15

  Kolossiatis, M ^a   Griffin, J E ^b   Steel, M F J ^c  

^a CYPRUS UNIVERSITY OF TECHNOLOGY   (Cyprus)

^b UNIVERSITY OF KENT   (United Kingdom)

^c UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

Dependent Dirichlet process; Markov chain Monte Carlo; Normalised random measures; P lya urn scheme; Split merge move

Indexed keywords

EID: 84872600070     PISSN: 09603174     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11222-011-9283-7     Document Type: Article

References (19)

1. Aigner, D., Lovell, C. A. K., Schmidt, P.: Formulation and estimation of stochastic frontier production function models. J. Econom. 6, 21-37 (1977).
2. Bernardo, J.-M., Smith, A. F. M.: Bayesian Theory. Wiley, Chichester (1994).
3. Cifarelli, D., Regazzini, E.: Problemi statistici non parametrici in condizioni di scambiabibilit? Parziale: impiego di medie associative. Technical Report, Quaderni Istituto di Matematica Finanziaria dell'Universita di Torino (1978).
4. De Iorio, M., Müller, P., Rosner, G. L., MacEachern, S. N.: An ANOVA model for dependent random measures. J. Am. Stat. Assoc. 99, 205-215 (2004).
5. Ferguson, T. S.: A Bayesian analysis of some nonparametric problems. Ann. Stat. 1, 209-230 (1973).
6. Fernández, C., Osiewalski, J., Steel, M. F. J.: On the use of panel data in stochastic frontier models with improper priors. J. Econom. 79, 169-193 (1997).
7. Griffin, J. E., Steel, M. F. J.: Semiparametric Bayesian inference for stochastic frontier models. J. Econom. 123, 121-152 (2004).
8. Griffin, J. E., Kolossiatis, M., Steel, M. F. J.: Comparing distributions with dependent normalized random measure mixtures. Technical Report, CRiSM Working Paper 10-24, University of Warwick (2010).
9. Hatjispyros, S. J., Nicoleris, T., Walker, S. G.: Dependent mixtures of dirichlet processes. Comput. Stat. Data Anal. 55, 2011-2025 (2011).
10. Ishwaran, H., Zarepour, M.: Series representations for multivariate generalized gamma processes via a scale invariance principle. Stat. Sin. 19, 1665-1682 (2009).
11. James, L., Lijoi, A., Prünster, I.: Posterior analysis for normalized random measures with independent increments. Scand. J. Stat. 36, 76-97 (2009).
12. Koop, G., Osiewalski, J., Steel, M. F. J.: Bayesian efficiency analysis through individual effects: hospital cost frontiers. J. Econom. 76, 77-105 (1997).
13. Leisen, F., Lijoi, A.: Vectors of two-parameter Poisson-Dirichlet processes, mimeo. J. Multivar. Anal. 102, 482-495 (2011).
14. Meeusen, W., van den Broeck, J.: Efficiency estimation from Cobb-Douglas production functions with composed error. Int. Econ. Rev. 18, 435-444 (1977).
15. Müller, P., Quintana, F., Rosner, G.: A method for combining inference across related nonparametric Bayesian models. J. R. Stat. Soc. B 66, 735-749 (2004).
16. Rao, V., Teh, Y. W.: Spatial normalized gamma processes. In: Bengio, Y., Schuurmans, D., Lafferty, J., Williams, C. K. I., Culotta, A. (eds.) Advances in Neural Information Processing Systems, vol. 22, pp. 1554-1562 (2009).
17. Teh, Y. W., Jordan, M. I., Beal, M. J., Blei, D. M.: Hierarchical Dirichlet processes. J. Am. Stat. Assoc. 101, 1566-1581 (2006).
18. Trippa, L., Müller, P., Johnson, W.: The multivariate beta process and an extension of the Pólya tree model. Biometrika 98, 17-34 (2011).
19. Walker, S. G., Muliere, P.: A bivariate Dirichlet process. Stat. Probab. Lett. 64, 1-7 (2003).