copula (version 0.5-8)

Mvdc: Multivariate Distribution via Copula

Description

Density, distribution function, and random generator for a multivariate distribution via copula.

Usage

mvdc(copula, margins, paramMargins)
dmvdc(mvdc, x)
pmvdc(mvdc, x)
rmvdc(mvdc, n)

Arguments

copula

an object of copula.

margins

a character vector specifying all the marginal distributions. See details below.

paramMargins

a list of list with names components, giving the parameter values of the marginal distributions. See details below.

mvdc

a mvdc object.

x

a vector of the copula dimension or a matrix with number of rows being the copula dimension, giving the coordinates of the points where the density of distribution function need to be evaluated.

n

number of observations to be generated.

Value

• 'mvdc' constructs an object of class "mvdc". 'dmvdc' gives the density, 'pmvdc' gives the distribution function, and 'rmvdc' generates random variates.

Details

The characters in argument margins are used to construct function names of density, distribution, and quantile functions. For example, "norm" can be used to specify marginal distribution, because "dnorm", "pnorm", and "qnorm" are all available.

Each component list in argument paramMargins is a list with named component which are used to specify the parameters of the marginal distributions. For example, paramMargins = list(list(mean = 0, sd = 2), list(rate = 2)) can be used to specify that the first margin is normal with mean 0 and sd 2, and the second margin is exponential with rate 2.

See Also

ellipCopula, archmCopula, mvdc-class, copula-class

Examples

## construct a bivariate distribution whose marginals
## are normal and exponential respectively, coupled
## together via a normal copula
x <- mvdc(normalCopula(0.75), c("norm", "exp"),
          list(list(mean = 0, sd =2), list(rate = 2)))
x.samp <- rmvdc(x, 100)
dmvdc(x, x.samp)
pmvdc(x, x.samp)
persp(x, dmvdc, xlim = c(-4, 4), ylim=c(0, 1))