create_priors: Create an object of class bcgppriors
In cbdavis33/bcgp: Bayesian Composite Gaussian Processes

Description Usage Arguments Details Value See Also Examples

create_priors returns an instance of S4 class bcgppriors

1 2	create_priors(composite = TRUE, stationary = FALSE, noise = FALSE, d = 1L)

`composite`	A logical, `TRUE` for a composite of a global process, a local process, and an error process, `FALSE` for non-composite. Defaults to `TRUE`.
`stationary`	A logical, `FALSE` for a non-stationary process, `TRUE` for a stationary process. If `FALSE`, the variance for the process is σ^2(x), and if `TRUE`, the variance is σ^2. Defaults to `FALSE`.
`noise`	If the data should be noise-free (such as from a deterministic computer model), then `noise` should be `FALSE`. Otherwise, it should be `TRUE`. Defaults to `FALSE`
`d`	An integer giving the dimension of the data.

This creates an instance of S4 class bcgppriors that contains default values for the priors, information about the process, and information about the distributions. The user can change the values as they like prior to fitting any data with bcgp. bcgppriors() can also be called to create a bcgppriors object.

An instance of S4 class bcgppriors containing the default values for all the prior parameters, information about the process, and information about the distributions.

bcgppriors bcgppriors bcgp