/src/main/java/net/finmath/optimizer/StochasticLevenbergMarquardt.java
isParameterCurrentDerivativeValid = false; lambda = lambdaInitialValue;
lambda = lambdaInitialValue; isParameterCurrentDerivativeValid = false;
parameterCurrent = initialParameters.clone(); valueTest = new RandomVariable[numberOfValues]; valueCurrent = new RandomVariable[numberOfValues]; Arrays.fill(valueCurrent, new RandomVariableFromDoubleArray(Double.NaN)); derivativeCurrent = new RandomVariable[numberOfParameters][numberOfValues]; iteration = 0; <extra_id_0> while(true) { iteration++; prepareAndSetValues(parameterTest, valueTest); final double errorMeanSquaredTest = getMeanSquaredError(valueTest); final boolean isPointAccepted = errorMeanSquaredCurrent > errorMeanSquaredTest; if(isPointAccepted) {