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 = 1e06,
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 1e6 .

name 
kernel function to be used. Either "sexp" for squared exponential kernel or
"matern2.5" for MatÃ©rn2.5 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/dgpsiR/.
Value
A 'python' object to represent a GP node.
Examples
## Not run:
# Check https://mingdeyu.github.io/dgpsiR/ for examples
# on how to customize DGP structures using kernel().
## End(Not run)
[Package
dgpsi version 2.1.5
Index]