"covComp"Class "covComp" representing a composite kernel combining
several kernels objects inheriting from the class "covAll".
Objects can be created by calls of the form new("covComp",
...) or by using covComp.
def:Object of class "expression" defining the
This is a parsed and cleaned version of the value
of the formula formal in covComp.
covAlls:Object of class "list" containing the kernel
objects used by the formula. The coefficients of these
kernels can be changed.
hasGrad:Object of class "logical": can we differentiate
the kernel w.r.t. all its parameters?
label:Object of class "character" A label attached to the kernel
to describe it.
d:Object of class "integer": dimension (or number of inputs).
parN:Object of class "integer": number of parameters.
parNames:Object of class "character": vector of parameter names. Its
length is in slot parN.
inputNames:Object of class "character": names of the inputs used by
the kernel.
topParN:Object of class "integer": number of top parameters.
topParNames:Object of class "character". Names of the top parameters.
topPar:Object of class "numeric". Values of the top parameters.
topParLower:Object of class "numeric". Lower bounds for the top
parameters.
topParUpper:Object of class "numeric". Upper bounds for the top
parameters.
parsedFormula:Object of class "list". Ugly draft for some slots to be
added in the next versions.
Class "covAll", directly.
signature(object = "covComp"): coerce object into a
list of covariance kernels, each inheriting from the virual class
"covAll". This is useful e.g., to extract the coefficients
or to plot a covariance component.
signature(object = "covComp", X = "data.frame"): check that
the inputs exist with suitable column names and suitable factor
content. The levels should match the prescribed levels. Returns a
matrix with the input columns in the order prescribed by
object.
signature(object = "covComp"): extract or replace the
vector of coefficients.
signature(object = "covComp"): extract the vector of Lower
or Upper bounds on the coefficients.
signature(object = "covComp"): return the vector of
scores, i.e. the derivative of the log-likelihood w.r.t. the
parameter vector at the current parameter values.
The covComp creator.