New version: MarkovKernels v0.3.0

[JuliaRegistrator]

• Registering package: MarkovKernels
• Repository: https://github.com/filtron/MarkovKernels.jl
• Created by: @filtron
• Version: v0.3.0
• Commit: 9335dc026aefa87e81af32eb06cc6a3f6b6abd0b
• Reviewed by: @filtron
• Reference: filtron/MarkovKernels.jl@9335dc0#commitcomment-151603842
• Description: Marginal distributions and Markov kernels that play nice with each other for the purpose of Bayesian state estimation.
• Release notes:

## Features

* Support for scalars as input/output of affine maps
* Support for Univariate Dirac/Normal distributions
* Costum types can now opt into being a valid representation of a PSD matrix by implementing ```psdcheck(::MyType) = IsPSD()``` and the accompanying interface
* Support for ``Ǹumber``` and ``ÙniformScaling```as PSD parametrizations.
* New type for representing Categorical distributions
* New type for representing Stochastic matrices
* New type for representing likelihood functions over categories
* New type for canonical parametrization of log-quadratic likelihood functions
* New function ```htransform``` for implementing backward likelihood recursions

## Breaking 

* ```sample_type``` instead of ```typeof_sample``` 
* ```sample_eltype``` instead of ```eltype_sample```

## docs

* Updated to showcase both forward and backward recursions for posterior inference. 

## Testing 

* Now testing against current Julia release
* Aqua tests
* JET tests

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