/src/main/java/net/finmath/montecarlo/templatemethoddesign/LogNormalProcess.java
final double previousValue = previouseRealization.get( pathIndex) ;final double diffusionOnPath = diffusionOfComponent.get( pathIndex) ;
final double diffusionOnPath = diffusionOfComponent.get ( pathIndex ) ;
final RandomVariable previouseRealization = discreteProcess[timeIndex-1][componentIndex]; for(int pathIndex = 0; pathIndex < numberOfPaths; pathIndex++) { final double previousValue = previouseRealization.get(pathIndex); final double driftOnPath = driftOfComponent.get(pathIndex); final double varianceOnPath = varianceOfComponent.get(pathIndex); <extra_id_0> newRealization[pathIndex] = previousValue * Math.exp(driftOnPath * deltaT - 0.5 * varianceOnPath * deltaT + diffusionOnPath); } discreteProcess[timeIndex][componentIndex] = new RandomVariableFromDoubleArray(getTime(timeIndex),newRealization); } if(scheme == Scheme.PREDICTOR_USING_EULERSTEP) { final RandomVariable[] newRealization = new RandomVariableFromDoubleArray[numberOfComponents];