bcgpMCMC: Draw samples from a bcgp model
In cbdavis33/bcgp1: Bayesian Composite Gaussian Processes

Description Usage Arguments Details Value See Also Examples

bcgpMCMC draws samples from the Bayesian Composite Gaussian Process model

1 2	bcgpMCMC(xTrain, yTrain, priors, inits, numUpdates, numAdapt, burnin, nmcmc)

`yTrain`	Avector containing the observed response values in the training set.
`numUpdates`	The number of updates in the proposal stepsize adaptation phase.
`numAdapt`	The number of samples within each update in the proposal stepsize adaptation phase.
`burnin`	The number of burnin samples to discard after the stepsize adaptation phase is finished
`X`	An `n x d` matrix containing the independent variables in the training set.
`prior`	A list containing the values for the prior parameters.

This draws samples from the posterior distribution for the Bayesian Composite Gaussian Process (BCGP) model.

An object of S4 class bcgp representing the fitted results.

Other Major functions: bcgp

xTrain <- matrix(runif(20, 0, 10), nrow = 10, ncol = 2)
yTrain <- xTrain[, 1] + sin(xTrain[, 2])
priors <- createPriors(noise = FALSE, d = 2)
bcgp(xTrain, yTrain, priors)