Inheritance diagram for NonDIncremLHSSampling:
Public Member Functions | |
| NonDIncremLHSSampling (Model &model) | |
| constructor | |
| ~NonDIncremLHSSampling () | |
| destructor | |
| void | quantify_uncertainty () |
| parameter samples, and computing statistics on the ensemble of results. | |
| void | print_results (ostream &s) |
| print the final statistics | |
Static Protected Member Functions | |
| static bool | rank_sort (const int &x, const int &y) |
| sort algorithm to compute ranks for rank correlations | |
Private Attributes | |
| int | previousSamples |
| number of samples in previous LHS run | |
| bool | varBasedDecompFlag |
| flags computation of VBD | |
Static Private Attributes | |
| static RealArray | rawData |
| vector to hold raw data before rank sort | |
The Latin Hypercube Sampling (LHS) package from Sandia Albuquerque's Risk and Reliability organization provides comprehensive capabilities for Monte Carlo and Latin Hypercube sampling within a broad array of user-specified probabilistic parameter distributions. The icremental LHS sampling capability allows one to supplement an initial sample of size n to size 2n while maintaining the correct stratification of the 2n samples and also maintaining the specified correlation structure. The icremental version of LHS will return a sample of size n, which when combined with the original sample of size n, allows one to double the size of the sample.
| NonDIncremLHSSampling | ( | Model & | model | ) |
constructor
This constructor is called for a standard letter-envelope iterator instantiation. In this case, set_db_list_nodes has been called and probDescDB can be queried for settings from the method specification.
| void quantify_uncertainty | ( | ) | [virtual] |
parameter samples, and computing statistics on the ensemble of results.
Generate incremental samples. Loop over the set of samples and compute responses. Compute statistics on the set of responses if statsFlag is set.
Implements NonD.
1.5.1