pith. sign in

arxiv: 1303.0439 · v1 · pith:AUR35HX6new · submitted 2013-03-03 · 📊 stat.ME

On Bayesian Nonparametric Continuous Time Series Models

classification 📊 stat.ME
keywords modelsbayesiancontinuousmodelnonparametricrequirementseriestime
0
0 comments X
read the original abstract

This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of model which meets this requirement. As it turns out, the model is well known in multiple change-point problems.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.