This is the complete list of members for GaussProcApproximation, including all inherited members.

add(const Pecos::SurrogateDataVars &sdv, bool anchor_flag)	Approximation	`[inline]`
add(const Variables &vars, bool anchor_flag, bool deep_copy)	Approximation
add(const Real *sample_c_vars, bool anchor_flag, bool deep_copy)	Approximation	`[inline]`
add(const RealVector &c_vars, const IntVector &di_vars, const RealVector &dr_vars, bool anchor_flag, bool deep_copy)	Approximation	`[inline]`
add(const Pecos::SurrogateDataResp &sdr, bool anchor_flag)	Approximation	`[inline]`
add(const Response &response, int fn_index, bool anchor_flag, bool deep_copy)	Approximation
addpoint(int, IntArray &added_index)	GaussProcApproximation	`[private]`
approx_rep() const	Approximation	`[inline]`
approxData	Approximation	`[protected]`
approxGradient	Approximation	`[protected]`
approxHessian	Approximation	`[protected]`
Approximation()	Approximation
Approximation(ProblemDescDB &problem_db, const SharedApproxData &shared_data)	Approximation
Approximation(const SharedApproxData &shared_data)	Approximation
Approximation(const Approximation &approx)	Approximation
Approximation(BaseConstructor, const ProblemDescDB &problem_db, const SharedApproxData &shared_data)	Approximation	`[protected]`
Approximation(NoDBBaseConstructor, const SharedApproxData &shared_data)	Approximation	`[protected]`
approximation_coefficients(bool normalized) const	Approximation	`[virtual]`
approximation_coefficients(const RealVector &approx_coeffs, bool normalized)	Approximation	`[virtual]`
approximation_data() const	Approximation	`[inline]`
approxPoint	GaussProcApproximation	`[private]`
approxValue	GaussProcApproximation	`[private]`
approxVariance	GaussProcApproximation	`[private]`
betaCoeffs	GaussProcApproximation	`[private]`
build()	GaussProcApproximation	`[protected, virtual]`
calc_grad_nll()	GaussProcApproximation	`[private]`
calc_nll()	GaussProcApproximation	`[private]`
challenge_diagnostics(const RealMatrix &challenge_points, int fn_index)	Approximation	`[virtual]`
cholFlag	GaussProcApproximation	`[private]`
clear_all()	Approximation	`[inline]`
clear_anchor()	Approximation	`[inline]`
clear_current()	Approximation	`[inline, virtual]`
clear_data()	Approximation	`[inline]`
clear_saved()	Approximation	`[inline]`
coefficient_labels(std::vector< std::string > &coeff_labels) const	Approximation	`[virtual]`
combine(short corr_type)	Approximation	`[virtual]`
constraint_eval(int mode, int n, const Teuchos::SerialDenseVector< int, double > &X, Teuchos::SerialDenseVector< int, double > &g, Teuchos::SerialDenseMatrix< int, double > &gradC, int &result_mode)	GaussProcApproximation	`[private, static]`
covMatrix	GaussProcApproximation	`[private]`
covSlvr	GaussProcApproximation	`[private]`
covVector	GaussProcApproximation	`[private]`
diagnostic(const String &metric_type)	Approximation	`[virtual]`
diagnostics_available()	Approximation	`[virtual]`
finalize()	Approximation	`[virtual]`
GaussProcApproximation()	GaussProcApproximation	`[inline]`
GaussProcApproximation(const SharedApproxData &shared_data)	GaussProcApproximation	`[inline]`
GaussProcApproximation(const ProblemDescDB &problem_db, const SharedApproxData &shared_data)	GaussProcApproximation
get_beta_coefficients()	GaussProcApproximation	`[private]`
get_cholesky_factor()	GaussProcApproximation	`[private]`
get_cov_matrix()	GaussProcApproximation	`[private]`
get_cov_vector()	GaussProcApproximation	`[private]`
get_grad_cov_vector()	GaussProcApproximation	`[private]`
get_process_variance()	GaussProcApproximation	`[private]`
get_trend()	GaussProcApproximation	`[private]`
GPinstance	GaussProcApproximation	`[private, static]`
GPmodel_apply(const RealVector &new_x, bool variance_flag, bool gradients_flag)	GaussProcApproximation	`[private]`
GPmodel_build()	GaussProcApproximation	`[private]`
gradCovVector	GaussProcApproximation	`[private]`
gradient(const Variables &vars)	GaussProcApproximation	`[protected, virtual]`
Dakota::Approximation::gradient(const RealVector &c_vars)	Approximation	`[virtual]`
gradNegLogLikTheta	GaussProcApproximation	`[private]`
hessian(const Variables &vars)	Approximation	`[virtual]`
hessian(const RealVector &c_vars)	Approximation	`[virtual]`
initialize_point_selection()	GaussProcApproximation	`[private]`
lhood_2d_grid_eval()	GaussProcApproximation	`[private]`
maxval(const RealArray &) const	GaussProcApproximation	`[private]`
min_coefficients() const	GaussProcApproximation	`[protected, virtual]`
min_points(bool constraint_flag) const	Approximation
negloglik(int mode, int n, const Teuchos::SerialDenseVector< int, double > &X, Real &fx, Teuchos::SerialDenseVector< int, double > &grad_x, int &result_mode)	GaussProcApproximation	`[private, static]`
negloglikNCSU(const RealVector &x)	GaussProcApproximation	`[private, static]`
normalize_training_data()	GaussProcApproximation	`[private]`
normTrainPoints	GaussProcApproximation	`[private]`
normTrainPointsAll	GaussProcApproximation	`[private]`
num_constraints() const	GaussProcApproximation	`[protected, virtual]`
numObs	GaussProcApproximation	`[private]`
numObsAll	GaussProcApproximation	`[private]`
operator=(const Approximation &approx)	Approximation
optimize_theta_global()	GaussProcApproximation	`[private]`
optimize_theta_multipoint()	GaussProcApproximation	`[private]`
pointsAddedIndex	GaussProcApproximation	`[private]`
pointsel_add_sel(const RealArray &delta)	GaussProcApproximation	`[private]`
pointsel_get_errors(RealArray &delta)	GaussProcApproximation	`[private]`
pointsel_write_points()	GaussProcApproximation	`[private]`
pop(bool save_data)	Approximation	`[virtual]`
pop_count(size_t count)	Approximation	`[inline]`
predict(bool variance_flag, bool gradients_flag)	GaussProcApproximation	`[private]`
prediction_variance(const Variables &vars)	GaussProcApproximation	`[protected, virtual]`
Dakota::Approximation::prediction_variance(const RealVector &c_vars)	Approximation	`[virtual]`
primary_diagnostics(int fn_index)	Approximation	`[virtual]`
print_coefficients(std::ostream &s, bool normalized)	Approximation	`[virtual]`
procVar	GaussProcApproximation	`[private]`
rebuild()	Approximation	`[virtual]`
recommended_coefficients() const	Approximation	`[virtual]`
recommended_points(bool constraint_flag) const	Approximation
restore()	Approximation	`[virtual]`
Rinv_YFb	GaussProcApproximation	`[private]`
run_point_selection()	GaussProcApproximation	`[private]`
set_bounds(const RealVector &c_l_bnds, const RealVector &c_u_bnds, const IntVector &di_l_bnds, const IntVector &di_u_bnds, const RealVector &dr_l_bnds, const RealVector &dr_u_bnds)	Approximation
sharedDataRep	Approximation	`[protected]`
store()	Approximation	`[virtual]`
thetaParams	GaussProcApproximation	`[private]`
trainMeans	GaussProcApproximation	`[private]`
trainPoints	GaussProcApproximation	`[private]`
trainStdvs	GaussProcApproximation	`[private]`
trainValues	GaussProcApproximation	`[private]`
trainValuesAll	GaussProcApproximation	`[private]`
trendFunction	GaussProcApproximation	`[private]`
trendFunctionAll	GaussProcApproximation	`[private]`
trendOrder	GaussProcApproximation	`[private]`
usePointSelection	GaussProcApproximation	`[private]`
value(const Variables &vars)	GaussProcApproximation	`[protected, virtual]`
Dakota::Approximation::value(const RealVector &c_vars)	Approximation	`[virtual]`
writeCovMat(char[])	GaussProcApproximation	`[private]`
writex(const char[])	GaussProcApproximation	`[private]`
~Approximation()	Approximation	`[virtual]`
~GaussProcApproximation()	GaussProcApproximation	`[inline]`