Usage
vine(data,K=8,lambda=100,pen=1,base="B-spline",m=2,cores=NULL,
q=2,test.ind=FALSE,test.ind1=FALSE,selec="cAIC",max.iter=51,RVM=NULL,
lam.vec=NULL,l.search=FALSE,fix.lambda=FALSE,id=NULL)
Arguments
data
'data' contains the data. 'data' has to be a matrix or a
data.frame with two columns.
K
K is the degree of the Bernstein polynomials. In the case of
linear B-spline basis functions, K+1 nodes are used for the basis functions.
lambda
Starting value for lambda, default is lambda=100.
pen
'pen' indicates the used penalty. 'pen=1' for the
difference penalty of m-th order. 'pen=2' is only implemented for
Bernstein polynomials, it is the penalty based
on the integrated squared second order derivatives of the Bernstein polynomials.
base
Type of basis function, default is
"B-spline". An alternative is base="Bernstein".
m
Indicating the order of differences to be penalised. Default is "m=2".
cores
Default=NULL, the number of cpu cores used for parallel computing can be specified.
q
Order of B-splines. Default is q=2, NULL if Bernstein polynomials are used.
test.ind
Default=FALSE, if TRUE each pair-copula starting in level 3 of the R-vine is tested for independence.
test.ind1
Default=FALSE, if TRUE each pair-copula in level 2 of the R-vine is tested for independence.
selec
Default="cAIC", determines the selection criteria of the vine structure. selec="ken.tau" chooses Kendells tau for selection.
max.iter
maximum number of iteration, the default is max.iter=51.
RVM
Default=NULL, RVM is RVine-Matrix determining the structure of the vine.
l.search
Default=FALSE, indicating if a search about several starting values for lambda should be performed. If search is selected, the starting value 'lambda' does not work anymore.
lam.vec
Vector of candidate values for penalty parameter lambda
fix.lambda
Default=FALSE, indicating if lambda is fixed or not.