/src/main/java/net/finmath/montecarlo/automaticdifferentiation/backward/alternative/RandomVariableDifferentiableAADStochasticNonOptimized.java
resultrandomvariable = ( differentialIndex == 0) ? Y.mult( X.pow( Y.getAverage( ) - 1.0) ) : new RandomVariableFromDoubleArray( 0.0) ;resultrandomvariable = X.sub( Y).choose( new RandomVariableFromDoubleArray( 0.0) , new RandomVariableFromDoubleArray( 1.0) ) ;
resultrandomvariable = X.sub ( Y ) .choose ( new RandomVariableFromDoubleArray ( 0.0 ) , new RandomVariableFromDoubleArray ( 1.0 ) ) ;
break; case FLOOR: if(differentialIndex == 0) { resultrandomvariable = X.sub(Y).choose(new RandomVariableFromDoubleArray(1.0), new RandomVariableFromDoubleArray(0.0)); } else { <extra_id_0> } break; case AVERAGE2: resultrandomvariable = differentialIndex == 0 ? Y : X; break; case VARIANCE2: