/src/main/java/net/finmath/montecarlo/automaticdifferentiation/backward/alternative/RandomVariableDifferentiableAADStochasticNonOptimized.java
resultrandomvariable = X.apply( derivative)  {
resultrandomvariable = X.apply ( new DoubleUnaryOperator ( ) {
break; case STDEV: resultrandomvariable = X.sub(X.getAverage()*(2.0*X.size()-1.0)/X.size()).mult(2.0/X.size()).mult(0.5).div(Math.sqrt(X.getVariance())); break; case MIN: final double min = X.getMin(); <extra_id_0> @Override public double applyAsDouble(final double x) { return (x == min) ? 1.0 : 0.0; } }); break;