Major changes
- Possibility to fit condition-wise by sharing stages, topologies and varying the number of events across conditions (see Tutorial 4)
- Estimates peak-to-peak latencies instead of onset-to-onset, this change does modify the duration of the first and last stage estimated by a magnitude of half an event width
- The minimum duration for a stage has been changed from a location imputed to the PDF of stage duration to a censoring of the number of samples corresponding to that duration.
- Added LOOCV method for any kind of fitted object
- Bootstrap now also accept any model and will bootstrap on any dimension
- Simulations can now be done on 'eeg'/'meg'/'eeg/meg' and at the desired sampling frequency
- Full support for an extended set of PDF: lognormal, Wald, Weibull, log-logistic, Chi
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Minor changes
- Added function to recover generating parameters and magnitudes
- improved cluster plots
- small fixes on the EM method
- Re-introduced penalty on the channel contribution
- Docstrings mostly present (except resample.py)
- compute_topologies is faster and can also be done on a moving average of the size of an event