Comments (2)
In principle yes, although there might be some identifiability issues if you try to estimate both prior cluster probabilities and prior state probabilities separately. It should be relatively straightforward modification to allow these, but it would need bit of coding nevertheless, and unfortunately at the moment we do not have resources to add new features to seqHMM. Pull requests are of course welcome.
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Thanks for the response. Your point about identifiability issues for MHMMs with cluster priors is well taken, I should have been more clear that I was hoping for priors for the HMM objects only. I don't currently have the time resources to add new features either, so I'll close this for now. Thanks for the great package, @helske!
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Related Issues (20)
- specifying emission matrix HOT 2
- [Help request] How to test the model? HOT 1
- can this package support Multivariate Discrete HMM?? HOT 3
- will it work for multivariate time series prediction : different continues or/and discrete/category observation HOT 4
- HMM cluster assignments HOT 2
- seqdata should be a state sequence object HOT 1
- Apply to financial time series? HOT 1
- Parsing HMMER3 files HOT 2
- 'System seems singular' and 'EM algorithm failed' for Mixture Markov Model HOT 2
- Building a model with different sequence lengths HOT 1
- hidden_paths does not respect sequence length HOT 4
- Parallel computation HOT 2
- Forward probability of MHMM vs HMM HOT 1
- standard errors for HMM parameters HOT 3
- Maximum number of colours in cpal/colorpalette HOT 4
- Extracting combinations of emitted states HOT 4
- Error in if (em.con$reltol < resEM$change) { : argument is of length zero HOT 5
- Absorbing state broken in `build_mm()` (seqhmm 1.2.1-1) HOT 1
- Runtime Estimation HOT 1
- EM algorithm failed HOT 1
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