Consider transfering the `ESSModel` to `AbstractMCMC`

[yebai]

We currently have a type ESSModel that implements a factorised version of logdensityproblem.

Now that we have the following new type, does it make sense to generalise and transfer the ESSModel type into this package?

AbstractMCMC.jl/src/logdensityproblems.jl

Lines 11 to 25 in 50cdf04

	- `logdensity`: The object that implements the LogDensityProblems.jl interface.
	"""
	struct LogDensityModel{L} <: AbstractModel
	logdensity::L
	function LogDensityModel{L}(logdensity::L) where {L}
	if LogDensityProblems.capabilities(logdensity) === nothing
	throw(
	ArgumentError(
	"The log density function does not support the LogDensityProblems.jl interface",
	),
	)
	end
	return new{L}(logdensity)
	end
	end

In addition, this factorisation is also helpful for other samplers like nested sampling (see NestedModel) and tempering methods (e.g. when we only temper the likelihood term).

cc @torfjelde @devmotion @mileslucas

[devmotion]

Maybe it would be better to not have a dedicated model but a special log density function type with the desired factorization that can be used in LogDensityModel. Then it should be possible to use the same model with e.g. EllipticalSliceSampling and AdvancedHMC.

[torfjelde]

I guess this is somewhat related to parts of the discussion in #85.

Maybe it would be better to not have a dedicated model but a special log density function type with the desired factorization that can be used in LogDensityModel.

This seems like a sensible approach 👍