University of Cambridge > Talks.cam > Statistics > Bayesian nonparametrics with heterogeneous data

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Bayesian nonparametrics with heterogeneous data

Download to your calendar using vCal

If you have a question about this talk, please contact .

The talk surveys some recent work on random probability measure vectors and their role in Bayesian statistics. Indeed, dependent nonparametric priors are useful tools for drawing inferences on data that arise from different studies or experiments and for which the usual exhangeability assumption is not satisfied. The presentation will focus on mixture models and their uses for density estimation and for the analysis of right-censored survival data. Some of the theoretical results to be presented are also relevant for devising Gibbs sampling schemes that will be applied to simulated and real datasets.

This talk is part of the Statistics series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Topological Solitons Basement conference room in person & via zoom

Other talks

"That's History. That's Truth. I Seen It Myself": T'tc~tsa (Wailaki) and the Enslavement of California Native Americans. TBC Beyond Hubble: Studying the Earliest Galaxies with the James Webb Space Telescope TBC Climate, uncertainty, and the slippery measurement of Antarctic ice Title to be confirmed
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity