Vine_Copula_Fit: C and D-vine Copula - Fitting
In rjaneUCF/MultiHazard-R-Package: Tools for modeling compound events

Description Usage Arguments Value See Also Examples

Fit either a C- or D-vine copula model. Function is a repackaging of the CDVineCopSelect function in the CDVine package.

1 2	Vine_Copula_Fit(Data, FamilySet = NA, Type = "DVine", SelCrit = "AIC", Indeptest = FALSE, Level = 0.05)

`Data`	Data frame containing `n` at least partially concurrent time series. First column may be a `"Date"` object. Can be `Dataframe_Combine` output.
`FamilySet`	Integer vector which must include at least one pair-copula family that allows for positive and one that allows for negative dependence. If `familyset = NA` (default), selection among all possible families is performed. The coding of pair-copula families is shown below. See help file of the `CDVineSim` function to find the integers representing the different copula families.
`Type`	Type of the vine model: 1 or "CVine" = C-vine 2 or "DVine" = D-vine
`SelCrit`	Character vector specifying the criterion for choosing among the competing pair-copula. Possible choices: `"AIC"` (default) or `"BIC"`.
`Indeptest`	Logical; whether a hypothesis test for the independence of `u1` and `u2` is performed before bivariate copula selection (default: `Indeptest = FALSE`; cp. BiCopIndTest). The independence copula is chosen for a (conditional) pair if the null hypothesis of independence cannot be rejected.
`level`	Numeric; significance level of the independence test (default: level = 0.05).

List comprising the pair-copula families composing the C- or D-vine copula Family, its parameters Par and Par2 as well as whether it is a C or D-vine Type.

Dataframe_Combine Vine_Copula_Sim CDVineCopSelect BiCopSelect

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S20.Vine<-Vine_Copula_Fit(Data=S20.Detrend.df, FamilySet=NA,
                          Type="DVine", SelCrit="AIC",
                          Indeptest=FALSE, Level=0.05)