Tools for Gaussian Process Modeling in Uncertainty Quantification

[Up] [Top]

Documentation for package ‘GPBayes’ version 0.1.0-6

Help Pages

GPBayes-package Tools for Gaussian Stochastic Process Modeling in Uncertainty Quantification
BesselK Modified Bessel function of the second kind
cauchy The generalized Cauchy correlation function
CH The Confluent Hypergeometric correlation function proposed by Ma and Bhadra (2023)
cor.to.par Find the correlation parameter given effective range
deriv_kernel A wraper to construct the derivative of correlation matrix with respect to correlation parameters
distance Compute distances for two sets of inputs
GaSP Building, fitting, predicting for a GaSP model
gp Construct the 'S4' object gp
gp-class The 'gp' class
gp.condsim Perform conditional simulation from a Gaussian process
gp.fisher Fisher information matrix
gp.get.mcmc get posterior summary for MCMC samples
gp.mcmc A wraper to fit a Gaussian stochastic process model with MCMC algorithms
gp.model.adequacy Model assessment based on Deviance information criterion (DIC), logarithmic pointwise predictive density (lppd), and logarithmic joint predictive density (ljpd).
gp.optim A wraper to fit a Gaussian stochastic process model with optimization methods
gp.predict Prediction at new inputs based on a Gaussian stochastic process model
gp.sim Simulate from a Gaussian stochastic process model
HypergU Confluent hypergeometric function of the second kind
ikernel A wraper to build different kinds of correlation matrices between two sets of inputs
kernel A wraper to build different kinds of correlation matrices with distance as arguments
loglik A wraper to compute the natural logarithm of the integrated likelihood function
matern The Matérn correlation function proposed by Matérn (1960)
powexp The powered-exponential correlation function
show,gp-methods Print the information an object of the 'gp' class
show-method Print the information an object of the 'gp' class