R: Initialize a Gaussian process node

kernel {dgpsi}

R Documentation

Initialize a Gaussian process node

Description

This function constructs a kernel object to represent properties of a Gaussian process node.

Usage

kernel(
  length,
  scale = 1,
  nugget = 1e-06,
  name = "sexp",
  prior_name = "ga",
  prior_coef = c(1.6, 0.3),
  nugget_est = FALSE,
  scale_est = FALSE,
  input_dim = NULL,
  connect = NULL
)

Arguments

`length`	a vector of lengthscales. The length of the vector equals to: either one if the lengthscales in the kernel function are assumed same across input dimensions; or the total number of input dimensions, which is the sum of the number of feeding GP nodes in the last layer (defined by the argument `input_dim`) and the number of connected global input dimensions (defined by the argument `connect`), if the lengthscales in the kernel function are assumed different across input dimensions.
`scale`	the variance of a GP node. Defaults to `1`.
`nugget`	the nugget term of a GP node. Defaults to `1e-6`.
`name`	kernel function to be used. Either `"sexp"` for squared exponential kernel or `"matern2.5"` for Matérn-2.5 kernel. Defaults to `"sexp"`.
`prior_name`	prior options for the lengthscales and nugget term. Either gamma (`"ga"`) or inverse gamma (`"inv_ga"`) distribution for the lengthscales and nugget term. Set `NULL` to disable the prior. Defaults to `"ga"`.
`prior_coef`	a vector that contains two values specifying the shape and rate parameters of the gamma prior, or shape and scale parameters of the inverse gamma prior. Defaults to `c(1.6,0.3)`.
`nugget_est`	set to `TRUE` to estimate the nugget term or to `FALSE` to fix the nugget term as specified by the argument `nugget`. If set to `TRUE`, the value set to the argument `nugget` is used as the initial value. Defaults to `FALSE`.
`scale_est`	set to `TRUE` to estimate the variance (i.e., scale) or to `FALSE` to fix the variance (i.e., scale) as specified by the argument `scale`. Defaults to `FALSE`.
`input_dim`	a vector that contains either the indices of GP nodes in the feeding layer whose outputs feed into this GP node; or the indices of global input dimensions that are linked to the outputs of some feeding emulators, if this GP node is in the first layer of a GP or DGP, which will be used for the linked emulation. When set to `NULL`, all outputs from the GP nodes in the feeding layer feed into this GP node; or all global input dimensions feed into this GP node. Defaults to `NULL`.
`connect`	a vector that contains the indices of dimensions in the global input connecting to this GP node as additional input dimensions. When set to `NULL`, no global input connection is implemented. Defaults to `NULL`. When this GP node is in the first layer of a GP or DGP emulator, which will consequently be used for linked emulation, `connect` gives the indices of global input dimensions that are not connected to some feeding emulators. In such a case, set `input_dim` to a vector of indices of the remaining input dimensions that are connected to the feeding emulators.

Details

See further examples and tutorials at https://mingdeyu.github.io/dgpsi-R/.

Value

A 'python' object to represent a GP node.

Examples

## Not run: 

# Check https://mingdeyu.github.io/dgpsi-R/ for examples
# on how to customize DGP structures using kernel().

## End(Not run)

[Package dgpsi version 2.1.5 Index]