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I am reading paper "Bayesian Online Changepoint Detection", which can be found at arxiv:

https://arxiv.org/pdf/0710.3742.pdf

The results looks inspiring, though it is unclear how to choose (or estimate) the parameters in the priors.

What could be a suitable way to estimate those parameters if one has some historical data?

The problem considered in the paper above is a case of Hidden Markov Models. The authors model the time periods (run lengths) between the changing points of some parameters in the time series.

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  • $\begingroup$ Please add relevant details to the body of the question, so that people do not need to read the whole article to understand your question. $\endgroup$ – Tim Jan 29 at 15:02
  • $\begingroup$ Dear @Tim, I have added some details. Thank you. $\endgroup$ – ABK Jan 29 at 15:10

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