Maxime Mouchet

Hi, Parameter estimation with multiple sequences (of potentially different lengths), is not currently supported in `HMMBase`. It's something that I would like to implement (in [mle.jl](https://github.com/maxmouchet/HMMBase.jl/blob/master/src/mle.jl)), but I don't know...

In HMMBase I make use of the `Distributions.jl` package for the `pdf` (likelihood) and `fit_mle` (parameter estimation) methods. This way I can handle any observations distributions that implement these methods....

By "responsibilities" I mean `P(Z_t = i | Y, θ)`, where `Z_t` is the hidden state at time t, `Y` the observations, and `θ` the model parameters.

You're right, it's possible to use the same scaling vector `c` for `α` and `β`. It's not done, for now, to keep the code simple :-)

No worries! This is the log-sum-exp trick : https://en.wikipedia.org/wiki/LogSumExp It prevents exp(LL[t,j]) from overflowing.

Nice! I recently cleaned-up the code by removing the `logl` keyword and the methods that do not use the log-likelihoods. Basically everything is done using the log-likelihoods now. Feel free...

I think the correct URL is https://nbviewer.jupyter.org/github/SosUts/HMMBase.jl/blob/multiple_sequences/notebooks/multiple%20sequences.ipynb :) This looks very nice! Thank you for your work :) You can open a PR now, and I'll review the code. It...

No worries, you can keep the PR open! Every commit that you add to your branch will be added to the PR automatically. I'm a bit busy this week, so...

I do not have the time anymore to review complex PRs to HMMBase, but if anyone feels like taking over maintenance for this repository, or promoting a fork with new...

Hi Guillaume, That sounds good to me! You're much more active in the Julia ecosystem than me :-) Honestly I'm open to anything regarding new features. Maybe we can have...