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Update MCMC and DREAM describtion
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thouska committed Apr 13, 2021
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4 changes: 2 additions & 2 deletions docs/Algorithm_guide.md
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Expand Up @@ -63,7 +63,7 @@ These steps are performed during the sampling:
* The best parameter set is taking after the burn-in as an inital parameter set for the Metropolis sampler
* A random value with a Gaussian distribution around the last best found parameter set is drawn to generate a new parameter-set (mean= last best parameter set, standard deviation=step-size of parameters function)
* Run simulation function with the new parameter set
* Calculate a hardcoded logProbability as likelihood
* Calculate a user defined likelihood function
* Decide if the new parameter is accepted through a Metropolis decision
* Save the last accepted run with likelihood, parameter set and simulation in a database

Expand Down Expand Up @@ -161,7 +161,7 @@ Like SCE-UA and SA, DE-MCz does not require any prior distribution information,
* Sample uniformly for all chains
* Generate a new parameter set
* Run simulation function with generated parameter sets
* Calculate a hardcoded logProbability as likelihood
* Calculate a user defined likelihood function
* Decide if the new parameter is accepted through a Metropolis decision
* Check convergence, if criterion is reached, stop

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