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Dakota  Version 6.2
Public Member Functions | Public Attributes | Protected Member Functions | Private Attributes | Static Private Attributes
NonDGPMSABayesCalibration Class Reference

Generates posterior distribution on model parameters given experiment data. More...

Inheritance diagram for NonDGPMSABayesCalibration:
NonDBayesCalibration NonDCalibration NonD Analyzer Iterator

List of all members.

Public Member Functions

 NonDGPMSABayesCalibration (ProblemDescDB &problem_db, Model &model)
 constructor
 ~NonDGPMSABayesCalibration ()
 destructor

Public Attributes

int emulatorSamples
 number of samples of the simulation to construct the GP
Real likelihoodScale
 scale factor for likelihood
bool calibrateSigmaFlag
 flag to indicated if the sigma terms should be calibrated (default true)
String approxImportFile
 name of file from which to import build points to build GP
unsigned short approxImportFormat
 build data import tabular format
bool approxImportActiveOnly
 import active variables only

Protected Member Functions

void derived_init_communicators (ParLevLIter pl_iter)
 derived class contributions to initializing the communicators associated with this Iterator instance
void derived_set_communicators (ParLevLIter pl_iter)
 derived class contributions to setting the communicators associated with this Iterator instance
void derived_free_communicators (ParLevLIter pl_iter)
 derived class contributions to freeing the communicators associated with this Iterator instance
void quantify_uncertainty ()
 performs a forward uncertainty propagation by using GPM/SA to generate a posterior distribution on parameters given a set of simulation parameter/response data, a set of experimental data, and additional variables to be specified here.

Private Attributes

Iterator lhsIter
 LHS iterator for generating samples for GP.

Static Private Attributes

static NonDGPMSABayesCalibrationNonDGPMSAInstance
 print the final statistics

Detailed Description

Generates posterior distribution on model parameters given experiment data.

This class provides a wrapper for the functionality provided in the Los Alamos National Laboratory code called GPM/SA (Gaussian Process Models for Simulation Analysis). Although this is a code that provides input/output mapping, it DOES NOT provide the mapping that we usually think of in the NonDeterministic class hierarchy in DAKOTA, where uncertainty in parameter inputs are mapped to uncertainty in simulation responses. Instead, this class takes a pre-existing set of simulation data as well as experimental data, and maps priors on input parameters to posterior distributions on those input parameters, according to a likelihood function. The goal of the MCMC sampling is to produce posterior values of parameter estimates which will produce simulation response values that "match well" to the experimental data. The MCMC is an integral part of the calibration. The data structures in GPM/SA are fairly detailed and nested. Part of this prototyping exercise is to determine what data structures need to be specified and initialized in DAKOTA and sent to GPM/SA, and what data structures will be returned.


Constructor & Destructor Documentation

NonDGPMSABayesCalibration ( ProblemDescDB problem_db,
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.

References Dakota::abort_handler(), Iterator::assign_rep(), NonDGPMSABayesCalibration::emulatorSamples, ProblemDescDB::get_string(), NonDGPMSABayesCalibration::lhsIter, NonDBayesCalibration::mcmcModel, Iterator::probDescDB, and NonDBayesCalibration::randomSeed.


Member Function Documentation

void quantify_uncertainty ( ) [protected, virtual]

Member Data Documentation

print the final statistics

Pointer to current class instance for use in static callback functions

Referenced by NonDGPMSABayesCalibration::quantify_uncertainty().


The documentation for this class was generated from the following files: