UncertaintyQuantification.jl
                                
                                
                                
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                        Bayesian updating framework
This is where I'll update/improve the framework to better integrate it into the existing code base.
Implemented right now are
- Metropolis Hastings 
mh() - Gibbs Sampler 
gibbssample() - Transitional MCMC 
tmcmc() - Sequential Monte Carlo 
smc() 
along with some helper methods.
To clean this up I would like to unify the interface somehow. My suggestion:
Have all methods called bayesian_inference() or some variation of it. These will take the values that are the same among all algorithms while the extra parameters are grouped into structs like
struct TransitionalMarkovChainMonteCarlo begin
    ...
end
struct SequentialMonteCarlo begin
    ...
end
For metropolis-hastings as well as tmcmc we would just wrap around TransitionalMCMC.jl if possible. No need to reinvent the wheel.
Ideally, the method signature would include the arguments that all of the methods have (if they exist). Like
function bayesian_model_updating(likelihood::Function, prior::Function, bmu::AbstractBayesianModelUpdating)
    ...
end
where the bmu includes everything else based on the method that should be used (Transitional, Sequential, MH, etc.). If that makes sense.
Having a common interface and grouping the extras in the struct seems fairly reasonable. Not 100% sure though.
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- Coverage   98.27%   80.95%   -17.32%     
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+ Hits         1027     1046       +19     
- Misses         18      246      +228     
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