| cokm {ARCokrig} | R Documentation |
Construct the cokm object
Description
This function constructs the cokm object in
autogressive cokriging models
Usage
cokm(
formula = list(~1, ~1),
output,
input,
cov.model = "matern_5_2",
nugget.est = FALSE,
prior = list(),
opt = list(),
NestDesign = TRUE,
tuning = list(),
info = list()
)
Arguments
formula |
a list of s elements, each of which contains the formula to specify fixed basis functions or regressors.
|
output |
a list of s elements, each of which contains a matrix of computer model outputs.
|
input |
a list of s elements, each of which contains a matrix of inputs.
|
cov.model |
a string indicating the type of covariance
function in AR-cokriging models. Current covariance functions include
- exp
product form of exponential covariance functions.
- matern_3_2
product form of Matern covariance functions with
smoothness parameter 3/2.
- matern_5_2
product form of Matern covariance functions with
smoothness parameter 5/2.
- Gaussian
product form of Gaussian covariance functions.
- powexp
product form of power-exponential covariance functions with roughness parameter fixed at 1.9.
|
nugget.est |
a logical value indicating whether the nugget is included or not. Default value is FALSE.
|
prior |
a list of arguments to setup the prior distributions with the reference prior as default.
- name
the name of the prior. Current implementation includes
JR, Reference, Jeffreys, Ind_Jeffreys
- hyperparam
hyperparameters in the priors.
For jointly robust (JR) prior, three parameters are included:
a refers to the polynomial penalty to avoid singular correlation
matrix with a default value 0.2; b refers to the exponenetial penalty to avoid
diagonal correlation matrix with a default value 1; nugget.UB is the upper
bound of the nugget variance with default value 1, which indicates that the
nugget variance has support (0, 1).
|
opt |
a list of arguments to setup the optim routine.
|
NestDesign |
a logical value indicating whether the
experimental design is hierarchically nested within each level
of the code.
|
tuning |
a list of arguments to control the MCEM algorithm for non-nested
design. It includes the arguments
- maxit
the maximum number of MCEM iterations.
- tol
a tolerance to stop the MCEM algorithm. If the parameter
difference between any two consecutive MCEM algorithm is less than
this tolerance, the MCEM algorithm is stopped.
- n.sample
the number of Monte Carlo samples in the
MCEM algorithm.
- verbose
a logical value to show the MCEM iterations if it is true.
|
info |
a list that contains
- iter
number of iterations used in the MCEM algorithm
- eps
parameter difference after the MCEM algorithm stops
|
Author(s)
Pulong Ma <mpulong@gmail.com>
See Also
ARCokrig, cokm.fit, cokm.predict
[Package
ARCokrig version 0.1.2
Index]