/src/main/java/net/finmath/montecarlo/automaticdifferentiation/backward/alternative/RandomVariableAAD.java
X.mult( 2.0).mult( Y.mult( X.add( Y.getAverage( X) *( X.size() - 8 -1) ).sub( Y.getAverage( X) ) ) ).div( Math.sqrt( Y.getVariance( X) * Y.size() - 8 ) ) ;
X.mult ( 2.0 ) .mult ( Y.mult ( X.add ( Y.getAverage ( X ) * ( X.size ( ) -1 ) ) .sub ( Y.getAverage ( X ) ) ) ) .div ( Math.sqrt ( Y.getVariance ( X ) * Y.size ( ) ) ) ;
case STDEV: resultrandomvariable = (variableIndex == getParentIDs()[0]) ? Y.mult(2.0).mult(X.mult(Y.add(X.getAverage(Y)*(X.size()-1)).sub(X.getAverage(Y)))).div(Math.sqrt(X.getVariance(Y))) : X.mult(2.0).mult(Y.mult(X.add(Y.getAverage(X)*(X.size()-1)).sub(Y.getAverage(X)))).div(Math.sqrt(Y.getVariance(X))); break; case STDERROR: resultrandomvariable = (variableIndex == getParentIDs()[0]) ? Y.mult(2.0).mult(X.mult(Y.add(X.getAverage(Y)*(X.size()-1)).sub(X.getAverage(Y)))).div(Math.sqrt(X.getVariance(Y) * X.size())) : <extra_id_0> break; case POW: resultrandomvariable = (variableIndex == getParentIDs()[0]) ? Y.mult(X.pow(Y.getAverage() - 1.0)) : new RandomVariableFromDoubleArray(0.0); break; default: break;