S4 class for kriging models.
To create a km
object, use km
. See also this function for more details.
d
:Object of class "integer"
. The spatial dimension.
n
:Object of class "integer"
. The number of observations.
X
:Object of class "matrix"
. The design of experiments.
y
:Object of class "matrix"
. The vector of response values at design points.
p
:Object of class "integer"
. The number of basis functions of the linear trend.
F
:Object of class "matrix"
. The experimental matrix corresponding to the evaluation of the linear trend basis functions at the design of experiments.
trend.formula
:Object of class "formula"
. A formula specifying the trend as a linear model (no response needed).
trend.coef
:Object of class "numeric"
. Trend coefficients.
covariance
:Object of class "covTensorProduct"
. See covTensorProduct-class
.
noise.flag
:Object of class "logical"
. Are the observations noisy?
noise.var
:Object of class "numeric"
. If the observations are noisy, the vector of noise variances.
known.param
:Object of class "character"
. Internal use. One of: "None", "All", "CovAndVar"
or "Trend"
.
case
:Object of class "character"
. Indicates the likelihood to use in estimation (Internal use). One of: "LLconcentration_beta", "LLconcentration_beta_sigma2", "LLconcentration_beta_v_alpha"
.
param.estim
:Object of class "logical"
. TRUE
if at least one parameter is estimated, FALSE
otherwise.
method
:Object of class "character"
. "MLE"
or "PMLE"
depending on penalty
.
penalty
:Object of class "list"
. For penalized ML estimation.
optim.method
:Object of class "character"
. To be chosen between "BFGS"
and "gen"
.
lower
:Object of class "numeric"
. Lower bounds for covariance parameters estimation.
upper
:Object of class "numeric"
. Upper bounds for covariance parameters estimation.
control
:Object of class "list"
. Additional control parameters for covariance parameters estimation.
gr
:Object of class "logical"
. Do you want analytical gradient to be used ?
call
:Object of class "language"
. User call reminder.
parinit
:Object of class "numeric"
. Initial values for covariance parameters estimation.
logLik
:Object of class "numeric"
. Value of the concentrated log-Likelihood at its optimum.
T
:Object of class "matrix"
. Triangular matrix delivered by the Choleski decomposition of the covariance matrix.
z
:Object of class "numeric"
. Auxiliary variable: see computeAuxVariables
.
M
:Object of class "matrix"
. Auxiliary variable: see computeAuxVariables
.
signature(x = "km")
Get the coefficients of the km
object.
signature(x = "km")
: see plot,km-method
.
signature(object = "km")
: see predict,km-method
.
signature(object = "km")
: see show,km-method
.
signature(object = "km")
: see simulate,km-method
.
km
for more details about slots and to create a km
object, covStruct.create
to construct a covariance structure, and covTensorProduct-class
for the S4 covariance class defined in this package.