gp.sim | R Documentation |
This function simulates realizations from Gaussian processes.
gp.sim(
formula = ~1,
input,
param,
cov.model = list(family = "CH", form = "isotropic"),
dtype = "Euclidean",
nsample = 1,
seed = NULL
)
formula |
an object of |
input |
a matrix including inputs in a GaSP |
param |
a list including values for regression parameters, covariance parameters, and nugget variance parameter. The specification of param should depend on the covariance model.
|
cov.model |
a list of two strings: family, form, where family indicates the family of covariance functions including the Confluent Hypergeometric class, the Matérn class, the Cauchy class, the powered-exponential class. form indicates the specific form of covariance structures including the isotropic form, tensor form, automatic relevance determination form.
|
dtype |
a string indicating the type of distance:
|
nsample |
an integer indicating the number of realizations from a Gaussian process |
seed |
a number specifying random number seed |
a numerical vector or a matrix
Pulong Ma mpulong@gmail.com
GPBayes-package, GaSP
, gp
n=50
y.sim = gp.sim(input=seq(0,1,length=n),
param=list(range=0.5,nugget=0.1,nu=2.5),
cov.model=list(family="matern",form="isotropic"),
seed=123)
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