CDVineCopulaConditional (version 0.1.1)

CDVineCondListMatrices: List of the possible C- and D- vines allowing for conditional simulation

Description

Provides a list of the C- and D- vines which allow for conditional sampling, under the condition discussed in the descriprion of CDVineCondFit.

Usage

CDVineCondListMatrices(data, Nx, type = "CVine-DVine")

Arguments

data

An N x d data matrix. Data of the conditioning variable(s) have to occupy the last column(s) of this matrix.

Nx

Number of conditioning variables.

type

Type of vine to be considered: C-Vine: "CVine" or 1; D-Vine: "DVine" or 2; Both C and D-Vine: "CVine-DVine" or "1-2" (default).

Value

Listes of matrices describing C- ($CVine) and D- ($DVine) Vines. Each matrix corresponds to a vine, according to the same notation used for RVineMatrix objects (for further details about RVineMatrix objects see the documentation file of the VineCopula package). The index i in the matrix corresponds to the variable in the i-th column of data.

References

Bevacqua, E., Maraun, D., Hobaek Haff, I., Widmann, M., and Vrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701-2723, https://doi.org/10.5194/hess-21-2701-2017, 2017. [link] [link]

Aas, K., Czado, C., Frigessi, A. and Bakken, H.: Pair-copula constructions of multiple dependence, Insurance: Mathematics and Economics, 44(2), 182-198, <doi:10.1016/j.insmatheco.2007.02.001>, 2009. [link]

See Also

CDVineCondFit

Examples

# NOT RUN {
# Read data
data(dataset)
data <- dataset$data[1:100,1:5]

# Define the variables Y and X. X are the conditioning variables, 
# which have to be positioned in the last columns of the data.frame
colnames(data) <- c("Y1","Y2","X3","X4","X5")

# List possible D-Vines:
ListVines <- CDVineCondListMatrices(data,Nx=3,"DVine")
ListVines$DVine

# List possible C-Vines:
ListVines <- CDVineCondListMatrices(data,Nx=3,"CVine")
ListVines$CVine

# List possible C- and D-Vines:
ListVines <- CDVineCondListMatrices(data,Nx=3,"CVine-DVine")
ListVines

# }