The previous procedure was using a fixed step size with a default value of 0.05 based on the suggestion by Marcel Van Oijen. The new procedure is using a change of the step size from an original value to a final value. Scaling of the start step size with the new default value of 0.5 is made based on a new switch in the Technical module. The Switch Marcov Chain Step contains 4 options: (1) Constant value, (2) Exponential decrease, (3) linear decrease and (4) a cyclic variation of the step size. New parameters are added to control the change of the step size as a function of number of runs during a multiple run. The BayesianMinScaling parameter determines the minimum step size by multiplication of the step size with the value of this parameter. The MC StepChangePeriod parameter determines the duration for change from max to min value for option (3) and (4) according to the switch settings of Marcov Chain Step. The change of the step size when using option (2) is regulated by the function f= exp(-k*no Runs) where k is the value of the parameter BayesianChangeCoef. A variation of the Marcov Chain step decrease the risk for a calibration to investigate a too small space of the parameter dimensions selected. A decrease of the step size will also increase the number of accepted runs since the search will be made closer the region that has a high probability according to Log Likelihood values.