bicop_dist: Bivariate copula models

In rvinecopulib: High Performance Algorithms for Vine Copula Modeling

Bivariate copula models

Description

Create custom bivariate copula models by specifying the family, rotation, parameters, and variable types.

Usage

bicop_dist(
  family = "indep",
  rotation = 0,
  parameters = numeric(0),
  var_types = c("c", "c")
)

Arguments

family	the copula family, a string containing the family name (see Details for all possible families).
rotation	the rotation of the copula, one of 0, 90, 180, 270.
parameters	a vector or matrix of copula parameters.
var_types	variable types, a length 2 vector; e.g., c("c", "c") for both continuous (default), or c("c", "d") for first variable continuous and second discrete.

Details

Implemented families

type	name	name in R
-	Independence	"indep"
Elliptical	Gaussian	"gaussian"
"	Student t	"student"
Archimedean	Clayton	"clayton"
"	Gumbel	"gumbel"
"	Frank	"frank"
"	Joe	"joe"
"	Clayton-Gumbel (BB1)	"bb1"
"	Joe-Gumbel (BB6)	"bb6"
"	Joe-Clayton (BB7)	"bb7"
"	Joe-Frank (BB8)	"bb8"
Nonparametric	Transformation kernel	"tll"

Value

An object of class bicop_dist, i.e., a list containing:

• family, a character indicating the copula family.

• rotation, an integer indicating the rotation (i.e., either 0, 90, 180, or 270).

• parameters, a numeric vector or matrix of parameters.

• npars, a numeric with the (effective) number of parameters.

• var_types, the variable types.

See Also

bicop_dist(), plot.bicop(), contour.bicop(), dbicop(), pbicop(), hbicop(), rbicop()

Examples

## Clayton 90° copula with parameter 3
cop <- bicop_dist("clayton", 90, 3)
cop
str(cop)

## visualization
plot(cop)
contour(cop)
plot(rbicop(200, cop))

## BB8 copula model for discrete data
cop_disc <- bicop_dist("bb8", 0, c(2, 0.5), var_types = c("d", "d"))
cop_disc

rvinecopulib documentation built on March 7, 2023, 6:20 p.m.