/src/main/java/net/finmath/montecarlo/automaticdifferentiation/backward/alternative/RandomVariableDifferentiableAADStochasticNonOptimized.java
resultrandomvariable = X.sub( X.getAverage( ) *( 2.0*X.size( ) -1.0) /X.size( ) ).mult( 2.0/X.size( ) ).mult( 2.0).div( Math.sqrt( X.getVariance( ) * X.size( ) ) ) ;
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 ( ) * X.size ( ) ) ) ;
}); break; case ABS: resultrandomvariable = X.choose(new RandomVariableFromDoubleArray(1.0), new RandomVariableFromDoubleArray(-1.0)); break; case STDERROR: <extra_id_0> break; case SVARIANCE: resultrandomvariable = X.sub(X.getAverage()*(2.0*X.size()-1.0)/X.size()).mult(2.0/(X.size()-1)); break; case ADD: resultrandomvariable = new RandomVariableFromDoubleArray(1.0);