R: Local Approximate Gaussian Process Regression

# Local Approximate Gaussian Process Regression

## Documentation for package ‘laGP’ version 1.5-10

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Code demos. Use demo() to run them.

## Help Pages

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