Several algorithms have changed their names, but also their role:

• MCMCSampling has become TransformedMCMC.

• MetropolisHastings has become RandomWalk. It's parameters have changed (no deprecation for the parameter changes). Tuning and sample weighting scheme selection have moved to TransformedMCMC.

• PriorToGaussian has become PriorToNormal.

Partial deprecations are available for the above, a lot of old code should run more or less unchanged (with deprecation warnings). Also:

• AdaptiveMHTuning has become AdaptiveAffineTuning, but is now used as a parameter for TransformedMCMC (formerly MCMCSampling) instead of RandomWalk (formerly MetropolisHastings).

• MCMCNoOpTuning has become NoMCMCTransformTuning.

• The parameters of HamiltonianMC have changed.

• MCMCTuningAlgorithm has been replaced by MCMCTransformTuning.

• The trafo parameter of algorithms has been renamed to pretransform, the trafo field in algorithm results has been renamed to f_pretransform.

• Sampling, integration and mode-finding algorithms now generate a return value result = ..., evaluated::EvaluatedMeasure = ..., ...) if their target is a probability measure/distribution.

• The new RAMTuning is now the default (transform) tuning algorithm for RandomWalk (formerly MetropolisHastings). It typically results in a much faster burn-in process than AdaptiveAffineTuning (formerly AdaptiveMHTuning, the previous default).

• MCMC Sampling handles parameter scale and correlation adaptivity via via tunable space transformations instead of tuning covariance matrices in proposal distributions.

• MCMC tuning has been split into proposal tuning (algorithms of type MCMCProposalTuning) and transform turning (algorithms of type MCMCTransformTuning). Proposal tuning has now a much more limited role and often may be NoMCMCProposalTuning() (e.g. for RandomWalk).

• Added MGVISampling for Metric Gaussian Variational Inference.

• AbstractVariateTransform and the function ladjof have been removed, BAT parameter transformations do not need to have a specific supertype any longer (see above).

• The new BATContext replaces passing rng::AbstractRNG random number generators around.

• Pending: LogDVal has been deprecated soon and will removed in BAT v3.1 or v3.2. Do not do this any longer:

  likelihood = let data = mydata
      function(v)
          log_likelihood_value = ...
          return LogDVal(log_likelihood_value)
      end
  end

  Instead, use the DensityInterface API (see above), like this:

  likelihood = let data = mydata
      logfuncdensity(function(v)
          log_likelihood_value = ...
          return log_likelihood_value
      end)
  end

  or like this

  struct MyLikeLihood{D}
      data::D
  end
  
  @inline DensityInterface.DensityKind(::MyLikeLihood) = IsDensity()
  
  function DensityInterface.logdensityof(likelihood::MyLikeLihood, v)
      log_likelihood_value = ...
      return log_likelihood_value
  end
  
  likelihood = MyLikeLihood(mydata)

  This allows for defining likelihoods without depending on BAT.

• New behavior of ValueShapes.NamedTupleShape and ValueShapes.NamedTupleDist: Due to changes in ValueShapes v0.10, NamedTupleShape and NamedTupleDist now either (by default) use NamedTuple or (optionally) ValueShapes.ShapedAsNT, but no longer a mix of them. As a result, the behavior of BAT has changed as well when using a NamedTupleDist as a prior. For example, mode(samples).result returns a NamedTuple now directly.

• SampledMeasure (formerly SampledDensity) have been replaced by EvaluatedMeasure.

• Some type-pirating prior plotting recipes have been removed, to be re-added in a clean way.

• Pending: BAT will rely less on ValueShapes in the future. Do not use ValueShapes functionality directly where avoidable. Use distprod instead of using ValueShapes.NamedTupleDist directly, and favor using bat_transform instead of shaping and unshaping data using values shapes directly, if possible.

• Use the new function bat_report to generate a sampling output report instead of show(BAT.SampledDensity(samples)).

• The field types of EvaluatedMeasure have changed.

• Support for DensityInterface: BAT will now accept any object that implements the DensityInterface API (specifically DensityInterface.densitykind and DensityInterface.logdensityof) as likelihoods. In return, all BAT priors and posteriors support the DensityInterface API as well.

• Support for InverseFunctions and ChangesOfVariables: Parameter transformations in BAT now implement the DensityInterface API. Any function that supports

  • InverseFunctions.inverse
  • ChangesOfVariables.with_logabsdet_jacobian
  • output_shape = f(input_shape::ValueShapes.AbstractValueShape)::AbstractValueShape

can now be used as a parameter transformation in BAT.

• BATContext, get_batcontext and set_batcontext

• bat_transform with enhanced capabilities

• distprod, distbind and lbqintegral are the new ways to express priors and posteriors in BAT.

• bat_report

• BAT.enable_error_log (experimental)

• BAT.error_log (experimental)

• BridgeSampling (experimental)

• EllipsoidalNestedSampling (experimental)

• ReactiveNestedSampling (experimental)