Man pages for hetGP
Heteroskedastic Gaussian Process Modeling and Design under Replication

allocate_multAllocation of replicates on existing designs
atoAssemble To Order (ATO) Data and Fits
bfsBayes Factor Data
compareGPLikelihood-based comparison of models
cov_genCorrelation function of selected type, supporting both...
crit_cSURContour Stepwise Uncertainty Reduction criterion
crit_EIExpected Improvement criterion
crit_ICUIntegrated Contour Uncertainty criterion
crit_IMSPESequential IMSPE criterion
crit_MCUMaximum Contour Uncertainty criterion
crit_optimCriterion optimization
crit_tMSEt-MSE criterion
deriv_crit_EIDerivative of EI criterion for GP models
deriv_crit_IMSPEDerivative of crit_IMSPE
ExpImpImport and export of hetGP objects
f1d1d test function
find_repsData preprocessing
hetGP-packagePackage hetGP
horizonAdapt horizon
IMSPEIntegrated Mean Square Prediction Error
IMSPE_optimIMSPE optimization
LOO_predsLeave one out predictions
mleHetGPGaussian process modeling with heteroskedastic noise
mleHetTPStudent-t process modeling with heteroskedastic noise
mleHomGPGaussian process modeling with homoskedastic noise
mleHomTPStudent-T process modeling with homoskedastic noise
predict.hetGPGaussian process predictions using a heterogeneous noise GP...
predict.hetTPStudent-t process predictions using a heterogeneous noise TP...
predict.homGPGaussian process predictions using a homoskedastic noise GP...
predict.homTPStudent-t process predictions using a homoskedastic noise GP...
SIRSIR test problem
update.hetGPUpdate '"hetGP"'-class model fit with new observations
update.hetTPUpdate '"hetTP"'-class model fit with new observations
update.homGPFast 'homGP'-update
update.homTPFast 'homTP'-update
WijCompute double integral of the covariance kernel over a...
hetGP documentation built on Jan. 10, 2019, 5:04 p.m.