In this release we have done the following additions and fixes:
- Added a DrawFromPrior inference scheme, with similar API as the other inference schemes and is used to sample from prior with no need to specify observation. That also has another method which can be used to generate simulation-parameter pairs to be used for learning the automatic summary statistics utilities.
- Added a method to the Journal which allows to resample the posterior samples (bootstrap and subsample). That generates a new journal which is returned by the method.
- Added a new
GenerateFromJournalclass which allows to generate simulations from a given model using parameter values stored in a journal. Together with the previous method this allows to perform predictive check. - Some reformatting to the Statistics; specifically, I've added the capability to standardize the different statistics by dividing them by their standard deviation on a set of reference simulations.
- Added the Statistics learning with exponential family based on Score Matching.
- Some refactoring of the Journal class
- Added option to not store the simulated dataset in the Journal for SMCABC. That breaks the possibility of restarting inference from the journal but greatly reduces journal size.
- Fixed the MCMC routine (used with BSL and others) when a starting point for the chain is passed.
- Added an example showing how to save to disk and re-load the learned neural network statistics.
- Some minor fixes in docs and tests.