| aGP | Localized Approximate GP Regression For Many Predictive Locations | 
| aGP.parallel | Localized Approximate GP Regression For Many Predictive Locations | 
| aGP.R | Localized Approximate GP Regression For Many Predictive Locations | 
| aGP.seq | Localized Approximate GP Regression For Many Predictive Locations | 
| aGPsep | Localized Approximate GP Regression For Many Predictive Locations | 
| aGPsep.R | Localized Approximate GP Regression For Many Predictive Locations | 
| alcGP | Improvement statistics for sequential or local design | 
| alcGPsep | Improvement statistics for sequential or local design | 
| alcoptGP | Improvement statistics for sequential or local design | 
| alcoptGPsep | Improvement statistics for sequential or local design | 
| alcrayGP | Improvement statistics for sequential or local design | 
| alcrayGPsep | Improvement statistics for sequential or local design | 
| blhs | Bootstrapped block Latin hypercube subsampling | 
| blhs.loop | Bootstrapped block Latin hypercube subsampling | 
| dalcGP | Improvement statistics for sequential or local design | 
| dalcGPsep | Improvement statistics for sequential or local design | 
| darg | Generate Priors for GP correlation | 
| deleteGP | Delete C-side Gaussian Process Objects | 
| deleteGPs | Delete C-side Gaussian Process Objects | 
| deleteGPsep | Delete C-side Gaussian Process Objects | 
| deleteGPseps | Delete C-side Gaussian Process Objects | 
| discrep.est | Estimate Discrepancy in Calibration Model | 
| distance | Calculate the squared Euclidean distance between pairs of points | 
| fcalib | Objective function for performing large scale computer model calibration via optimization | 
| fishGP | Improvement statistics for sequential or local design | 
| garg | Generate Priors for GP correlation | 
| ieciGP | Improvement statistics for sequential or local design | 
| ieciGPsep | Improvement statistics for sequential or local design | 
| jmleGP | Inference for GP correlation parameters | 
| jmleGP.R | Inference for GP correlation parameters | 
| jmleGPsep | Inference for GP correlation parameters | 
| jmleGPsep.R | Inference for GP correlation parameters | 
| laGP | Localized Approximate GP Prediction At a Single Input Location | 
| laGP.R | Localized Approximate GP Prediction At a Single Input Location | 
| laGPsep | Localized Approximate GP Prediction At a Single Input Location | 
| laGPsep.R | Localized Approximate GP Prediction At a Single Input Location | 
| llikGP | Calculate a GP log likelihood | 
| llikGPsep | Calculate a GP log likelihood | 
| mleGP | Inference for GP correlation parameters | 
| mleGPsep | Inference for GP correlation parameters | 
| mleGPsep.R | Inference for GP correlation parameters | 
| mspeGP | Improvement statistics for sequential or local design | 
| newGP | Create A New GP Object | 
| newGPsep | Create A New GP Object | 
| optim.auglag | Optimize an objective function under multiple blackbox constraints | 
| optim.efi | Optimize an objective function under multiple blackbox constraints | 
| predGP | GP Prediction/Kriging | 
| predGPsep | GP Prediction/Kriging | 
| randLine | Generate two-dimensional random paths | 
| updateGP | Create A New GP Object | 
| updateGPsep | Create A New GP Object |