Latent Stick-Breaking Processes.

Journal Article (Journal Article)

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 using a latent Gaussian copula model as the mechanism for selecting the atoms. The resulting latent stick-breaking process (LaSBP) induces a random partition of the index space, with points closer in space having a higher probability of being in the same cluster. We develop an efficient and straightforward Markov chain Monte Carlo (MCMC) algorithm for computation and discuss applications in financial econometrics and ecology. This article has supplementary material online.

Full Text

Duke Authors

Cited Authors

  • Rodríguez, A; Dunson, DB; Gelfand, AE

Published Date

  • April 2010

Published In

Volume / Issue

  • 105 / 490

Start / End Page

  • 647 - 659

PubMed ID

  • 23559690

Pubmed Central ID

  • PMC3614377

Electronic International Standard Serial Number (EISSN)

  • 1537-274X

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1198/jasa.2010.tm08241


  • eng