/src/main/java/net/finmath/montecarlo/interestrate/products/components/Option.java
filteredRegressionBasisFunctions[i] = regressionBasisFunctions[i].mult( strikePrice) ;
filteredRegressionBasisFunctions[i] = regressionBasisFunctions[i].mult ( filter ) ;
.mult(exerciseTrigger.sub(exerciseTriggerCap).mult(-1.0).choose(one, zero)); filter = filter.mult(filterNaN); exerciseTrigger = exerciseTrigger.mult(filter); final RandomVariable[] regressionBasisFunctions = regressionBasisFunctionsProvider != null ? regressionBasisFunctionsProvider.getBasisFunctions(evaluationTime, model) : getBasisFunctions(exerciseDate, model); final RandomVariable[] filteredRegressionBasisFunctions = new RandomVariable[regressionBasisFunctions.length]; for(int i=0; i<regressionBasisFunctions.length; i++) { <extra_id_0> } final ConditionalExpectationEstimator conditionalExpectationOperator = new MonteCarloConditionalExpectationRegression(filteredRegressionBasisFunctions, regressionBasisFunctions); exerciseTrigger = exerciseTrigger.getConditionalExpectation(conditionalExpectationOperator); } if(strikeProduct != null) { values = exerciseTrigger.choose(values, strikeProduct.getValue(exerciseDate, model));