RegressionBasisFunctionsFromProducts (finmath lib 5.0.5 API)

java.lang.Object
- net.finmath.montecarlo.conditionalexpectation.RegressionBasisFunctionsFromProducts

All Implemented Interfaces:

RegressionBasisFunctionsProvider
```
public class RegressionBasisFunctionsFromProducts
extends Object
implements RegressionBasisFunctionsProvider
```
An implementation of an RegressionBasisFunctionsProvider using a list of AbstractMonteCarloProduct-s. The getBasisFunctions method will perform a check if the products getValue method returns an \( \mathcal{F}_{t} \)-measurable random variable if called with evaluationTime being \( t \). If this test fails an IllegalArgumentException exception is thrown.

Version:

1.0

Author:

Christian Fries

Constructor Summary

Constructors
Constructor Description

RegressionBasisFunctionsFromProducts(List<AbstractMonteCarloProduct> products)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`RandomVariable[]`	`getBasisFunctions(double evaluationTime, MonteCarloSimulationModel model)`	Provides a set of \( \mathcal{F}_{t} \)-measurable random variables which can serve as regression basis functions.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - RegressionBasisFunctionsFromProducts
```
public RegressionBasisFunctionsFromProducts(List<AbstractMonteCarloProduct> products)
```
- Method Detail
  - getBasisFunctions
```
public RandomVariable[] getBasisFunctions(double evaluationTime,
                                          MonteCarloSimulationModel model)
```
    Description copied from interface: RegressionBasisFunctionsProvider
    
    Provides a set of \( \mathcal{F}_{t} \)-measurable random variables which can serve as regression basis functions.
    
    Specified by:
    
    getBasisFunctions in interface RegressionBasisFunctionsProvider
    
    Parameters:
    
    evaluationTime - The evaluation time \( t \) at which the basis function should be observed.
    
    model - The Monte-Carlo model used to derive the basis function.
    
    Returns:
    
    An \( \mathcal{F}_{t} \)-measurable random variable.