On Bayesian Nonparametric Continuous Time Series Models
Methodology
2013-03-05 v1
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.
Cite
@article{arxiv.1303.0439,
title = {On Bayesian Nonparametric Continuous Time Series Models},
author = {George Karabatsos and Stephen G. Walker},
journal= {arXiv preprint arXiv:1303.0439},
year = {2013}
}
Comments
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