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I started to play with you very nice library and I was surprised by to get a positive log likelihood
I used as basis an harmonic model with 3 sin and cos pairs to model a timeseries, while I left …
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This is a ticket that is similar to SN likelihood, only that it operates with the time-delay distances, there is no marginalization over the absolute amplitude. Sufficiently different that it needs to…
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# Documentation/tutorial notebooks
As of `2.9.1`, the `log_marginal_likelihood` is deprecated.
See the docs [here](https://gpflow.github.io/GPflow/2.9.1/api/gpflow/models/gpr/index.html#gpflow.mo…
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Hi! I'm working on modifying MontePython with an HMC/NUTS solver, which requires getting the gradient of loglkl. I would like to use candl for the CMB data, but I don't see a function that would direc…
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I probably need a lower level, C++ implementation of log likelihood.
I found this C++ package (maybe there are better options): http://www.cahillsoftware.com/media/af21843f135214fffff850fffffe417.…
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I am working on device failure detection using logs and trying to use HSMM for the same (https://github.com/mattjj/pyhsmm ). I have trained HSMM models one with failure sequences and another with non-…
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I'm posting this issue as a place to discuss and think about our strategy for likelihood-based inference for generalized linear mixed models. Right now I've got a working likelihood function for a Mix…
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Hey, ich habe die Test Log-likelihoods für den Boston Housing Datensatz berechnet, kann allerdings nicht die Ergebnisse der anderen Paper erreichen. Kannst du kurz einen Blick hier auf die Implementie…
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The broader question is whether it would not be clearer to define S3 methods for `numeric`, `epichains` and `epichains_summary` where
```r
likelihood.epichains
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https://adamhu.github.io/2019/06/Maximum-Likelihood-Estimation/