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

Bayesian inference using the DREAM approach. More...

Inheritance diagram for NonDDREAMBayesCalibration:
NonDBayesCalibration NonDCalibration NonD Analyzer Iterator

List of all members.

Public Member Functions

 NonDDREAMBayesCalibration (ProblemDescDB &problem_db, Model &model)
 standard constructor
 ~NonDDREAMBayesCalibration ()
 destructor

Static Public Member Functions

static void problem_size (int &chain_num, int &cr_num, int &gen_num, int &pair_num, int &par_num)
 initializer for problem size characteristics in DREAM
static void problem_value (std::string *chain_filename, std::string *gr_filename, double &gr_threshold, int &jumpstep, double limits[], int par_num, int &printstep, std::string *restart_read_filename, std::string *restart_write_filename)
 Filename and data initializer for DREAM.
static double prior_density (int par_num, double zp[])
 Compute the prior density at specified point zp.
static double * prior_sample (int par_num)
 Sample the prior and return an array of parameter values.
static double sample_likelihood (int par_num, double zp[])
 Likelihood function for call-back from DREAM to DAKOTA for evaluation.

Protected Member Functions

void quantify_uncertainty ()
 redefined from DakotaNonD

Protected Attributes

Real likelihoodScale
 scale factor for proposal covariance
bool calibrateSigma
 flag to indicate if the sigma terms should be calibrated (default true)
RealVector paramMins
 lower bounds on calibrated parameters
RealVector paramMaxs
 upper bounds on calibrated parameters
int numChains
 number of concurrent chains
int numGenerations
 number of generations
int numCR
 number of CR-factors
int crossoverChainPairs
 number of crossover chain pairs
Real grThreshold
 threshold for the Gelmin-Rubin statistic
int jumpStep
 how often to perform a long jump in generations
std::vector< boost::math::uniform > priorDistributions
 uniform prior PDFs for each variable
boost::mt19937 rnumGenerator
 random number engine for sampling the prior
std::vector
< boost::uniform_real< double > > 
priorSamplers
 samplers for the uniform prior PDFs for each variable

Static Private Attributes

static NonDDREAMBayesCalibrationNonDDREAMInstance
 Pointer to current class instance for use in static callback functions.

Detailed Description

Bayesian inference using the DREAM approach.

This class performed Bayesian calibration using the DREAM (Markov Chain Monte Carlo acceleration by Differential Evolution) implementation of John Burkhardt (FSU), adapted from that of Guannan Zhang (ORNL)


Constructor & Destructor Documentation

NonDDREAMBayesCalibration ( ProblemDescDB problem_db,
Model model 
)

standard 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 NonDDREAMBayesCalibration::crossoverChainPairs, NonDDREAMBayesCalibration::grThreshold, NonDDREAMBayesCalibration::jumpStep, NonDDREAMBayesCalibration::numChains, NonDDREAMBayesCalibration::numCR, NonDDREAMBayesCalibration::numGenerations, and NonDBayesCalibration::numSamples.


Member Function Documentation

void problem_size ( int &  chain_num,
int &  cr_num,
int &  gen_num,
int &  pair_num,
int &  par_num 
) [static]
void problem_value ( std::string *  chain_filename,
std::string *  gr_filename,
double &  gr_threshold,
int &  jumpstep,
double  limits[],
int  par_num,
int &  printstep,
std::string *  restart_read_filename,
std::string *  restart_write_filename 
) [static]
double prior_density ( int  par_num,
double  zp[] 
) [static]

Compute the prior density at specified point zp.

See documentation in DREAM examples)

References NonDDREAMBayesCalibration::NonDDREAMInstance, and NonDDREAMBayesCalibration::priorDistributions.

double * prior_sample ( int  par_num) [static]

Sample the prior and return an array of parameter values.

See documentation in DREAM examples)

References NonDDREAMBayesCalibration::NonDDREAMInstance, NonDDREAMBayesCalibration::priorSamplers, and NonDDREAMBayesCalibration::rnumGenerator.

double sample_likelihood ( int  par_num,
double  zp[] 
) [static]
void quantify_uncertainty ( ) [protected, virtual]

Member Data Documentation

Real likelihoodScale [protected]

scale factor for proposal covariance

scale factor for likelihood

Referenced by NonDDREAMBayesCalibration::sample_likelihood().


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