Locally Induced Gaussian Process Regression

Documentation for package ‘liGP’ version 1.0.1

borehole	Borehole equation data generator
build_gauss_measure_ipTemplate	Inducing point template design for a Gaussian measure built through sequential optimization
build_ipTemplate	Inducing point template design built through sequential optimization
build_neighborhood	Nearest Neighbor (NN) data subset given a center
calc_IMSE	Integrated Mean-Square Error Given a New Inducing Point
calc_wIMSE	Weighted Integrated Mean-Square Error Given a New Inducing Point
giGP	Global Inducing Point Approximate GP Regression For Many Predictive Locations
herbtooth	Herbie's Tooth function
liGP	Localized Inducing Point Approximate GP Regression For Many Predictive Locations
liGP.forloop	Localized Inducing Point Approximate GP Regression For Many Predictive Locations
liGP_gauss_measure	Localized Inducing Point Approximate GP Regression For a Gaussian Measure
loiGP	Locally Optimized Inducing Point Approximate GP Regression For Many Predictive Locations
optIP.ALC	Sequential Selection of an Inducing Point Design by Optimizing Active Learning Cohn
optIP.wIMSE	Sequential Selection of an Inducing Point Design by Optimizing Weighted Integrates Mean-Sqaure Error
qnormscale	Scaling of Inducing Point Design based on Inverse Gaussian CDF
scale_gauss_measure_ipTemplate	Inducing points design scaling for a Gaussian measure local neighborhood template
scale_ipTemplate	Inducing points design scaling for a local neighborhood template