Bayesian online changepoint detection for multivariate data

Question

Bayesian online changepoint detection for multivariate data

sokolov-alex opened this issue 9 years ago · 16 comments

Is it possible to make Ryan Adams algorithm to work on multivariate data too?

Answer 1 · 2016-01-13T09:32:53.000Z

As far as I can see, the change should be relatively easy, but a bit time consuming. It's only updating the student t distribution to handle multivariate data correctly. It is not yet in scipy, though, AFAIK, so it would need a bit of time to get it in there.

Would you feel confident enough to translate e.g. the wiki article on multivariate student t distributions to a scipy.stats.multivariate_t?

Answer 2 · 2016-01-13T17:45:43.000Z

I have found a multivariate student t distribution implementation, but I didn't yet find out how to change the update_theta function to handle multivariate data.

Answer 3 · 2016-01-13T17:46:33.000Z

You would want to mimic numpy.random.multivariate_normal as that is the main call from scipy.stats.multivariate_normal (the rest is type and size checking). If we just want a local version, that should be fine.

Answer 4 · 2017-04-22T17:53:08.000Z

Hi @sokolov-alex : Did you find a way to update the theta function?

Answer 5 · 2017-11-10T12:53:13.000Z

Depending on your goal it might be good enough to implement a multivariate T, which assumes the input variables to be independent. Though this will not capture a change in covariance structure, it might still be useful depending on what you are looking for. On top of that the implementation of this is rather simple.

Answer 6 · 2018-07-02T17:06:56.000Z

Hello friends, as I can see: Modeling Changing Dependency Structure in
Multivariate Time Series
So you already added this functionality to detect a change in multivariate time series?
it would great to have it.
Let's say I have 9 time series and small change happen in which of them. This change is not enough to detect by analyzing each one individually, but some aggregation may help?
Or 5 of them changed and 4 not, so still change will be detected with some probability ?

Answer 7 · 2020-08-04T09:42:33.000Z

Hi all!
Are there any changes?

Answer 8 · 2020-08-14T12:26:48.000Z

Good question

Answer 9 · 2021-01-25T05:45:02.000Z

I note that, as of this month, scipy now includes an implementation of the PDF for the multivariate t-distribution: https://docs.scipy.org/doc/scipy/reference/release.1.6.0.html#scipy-stats-improvements.

Does that make this easy to implement?

Answer 10 · 2021-01-25T06:51:38.000Z

I've also found an R implementation of this algorithm that works on multivariate data, which I think could be used as a meaningful reference. In particular, their "update theta" function is here: <deleted as from GPLv3 licensed code>

Answer 11 · 2021-01-25T06:58:14.000Z

Their code is GPL while this is MIT licence. Make sure you do not port! Generally, I don't have time to look at this right now, but I'm happy to merge PRs.

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On Mon, Jan 25, 2021, at 7:51 AM, Michael Milton wrote: I've also found an R implementation of this algorithm that works on multivariate data, which I think could be used as a meaningful reference. In particular, their "update theta" function is here: https://github.com/cran/ocp/blob/890dc2e075d5f310f1ace662bf7e25520d88a2c5/R/gaussian.R#L82-L112 — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#11 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAAVBVEZYG2TP7JRORUQGILS3UIIRANCNFSM4BYKW6NA>.

Answer 12 · 2021-01-25T07:03:37.000Z

We're doing some low level optimizations, so it might be hard to transfer those to the multivariate case, especially using a lib version (we basically implemented the distribution manually), but if you're interested go for it.

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On Mon, Jan 25, 2021, at 6:45 AM, Michael Milton wrote: I note that, as of this month, scipy now includes an implementation of the PDF for the multivariate t-distribution: https://docs.scipy.org/doc/scipy/reference/release.1.6.0.html#scipy-stats-improvements. Does that make this easy to implement? — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#11 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAAVBVBQECTIOP6XE457Z6LS3UAOXANCNFSM4BYKW6NA>.

Answer 13 · 2021-01-27T03:18:59.000Z

I reckon I can give this a shot. Is it okay to reference a book or paper for the maths without breaking the MIT license?

Answer 14 · 2021-01-27T05:51:04.000Z

Papers and math are totally fine.

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On Wed, Jan 27, 2021, at 4:19 AM, Michael Milton wrote: I reckon I can give this a shot. Is it okay to reference a book or paper for the maths without breaking the MIT license? — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#11 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAAVBVA4VGH4RGSV2WKVEP3S36A3BANCNFSM4BYKW6NA>.

Answer 15 · 2021-01-27T07:59:08.000Z

Draft PR in #26. Happy if anyone with a better grasp of the stats runs an eye over my code.

Answer 16 · 2021-03-14T09:09:40.000Z

Can we now close this issue as #26 has been merged?