Now showing items 1-4 of 4
Latent Stick-Breaking Processes.
(J Am Stat Assoc, 2010-04-01)
We develop a model for stochastic processes with random marginal distributions. Our model relies on a stick-breaking construction for the marginal distribution of the process, and introduces dependence across locations by ...
Bayesian generalized product partition model
(Statistica Sinica, 2010-07-01)
Starting with a carefully formulated Dirichlet process (DP) mixture model, we derive a generalized product partition model (GPPM) in which the partition process is predictor-dependent. The GPPM generalizes DP clustering ...
Dynamic nonparametric bayesian models for analysis of music
(Journal of the American Statistical Association, 2010-06-01)
The dynamic hierarchical Dirichlet process (dHDP) is developed to model complex sequential data, with a focus on audio signals from music. The music is represented in terms of a sequence of discrete observations, and the ...
Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.
(BMC Bioinformatics, 2010-11-09)
BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques ...