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Probabilistic Inference on Noisy Time Series
As per SMC (and per Radford Neal's AIS article on p10: ftp://www.cs.toronto.edu/pub/radford/ais-rev.pdf)
Both methods take the same arguments. Indeed, looking at the two classes, they're both virtually identical. They both use `model.n_parameters()` to check that the user has provided an object of...
- Replace "Using PINTS" in github readme with something longer, and called "Getting started" - Ensure this works with github dark theme (watch our for transparent PNGs!) - Make sure...
There are a number of log-likelihoods which would be useful (this came up in discussion for the [PKPD app](https://github.com/pkpdapp-team/pkpdapp).): - [x] log-normal: used a lot in PKPD modelling and elsewhere...
So add a "Running a Nested Sampling routine" file, which has the controller in it (it's currently in with base classes).
Closes #1137 The algorithm is largely the same as the existing a `pints.HamiltonianMCMC`. I made references in the ask and tell methods where the code has been adapted. The other...
- @fcooper8472 suggests last supported + 1 - Balance: Don't cut off support to soon, leave people stranded VS don't spend ages on making old stuff work - https://www.python.org/dev/peps/pep-0602/ -...
The ask-and-tell interface (#132) takes care of part of this, but it'd also be good to store the internal state of our optimisers/inferers to disk, perhaps using [pickling](https://docs.python.org/3/library/pickle.html) ?
When using multiprocessing, there are [different ways to start processes](https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods) and it can matter which on you choose. (For example, it took me most of yesterday to find out that...