From 6be2dcfa17e34e65dd43bf9f369da39c597d5760 Mon Sep 17 00:00:00 2001 From: thouska Date: Tue, 13 Apr 2021 15:10:00 +0200 Subject: [PATCH] Update MCMC and DREAM describtion --- docs/Algorithm_guide.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/Algorithm_guide.md b/docs/Algorithm_guide.md index 027f769e..e9b61128 100644 --- a/docs/Algorithm_guide.md +++ b/docs/Algorithm_guide.md @@ -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 @@ -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