The INI has a new website!

This is a legacy webpage. Please visit the new site to ensure you are seeing up to date information.

Skip to content

BNR

Seminar

Double Dirichlet process mixtures

Basu, S (Northern Illinois)
Friday 10 August 2007, 10:00-11:00

Seminar Room 1, Newton Institute

Abstract

In this work we consider a new class of Dirichlet process mixtures, that we call the double and multple DPM class, which generates a clustering structure in the data that is different from those generated by simple DPM or other DPM models. Fitting of double and related DPM models is possible by MCMC methods by multiple applications of the standard Polya urn and blocked Gibbs samplers within each sweep of the sampling. Based on experimental investigations we show that the proposed model performs reasonably well when the model is correctly specified and when the model is misspecified. We also investigate the similarity between the clustering produced by the model fit and the true clustering. Finally, we consider model comparison and model diagnostics, and illustrate the implementation, performance and applicability of the proposed class of DPM models in regressions for survival data and clustered longitudinal data.

Presentation

[ppt ]

Audio

MP3MP3

Back to top ∧