copula (version 0.999-7)

Mvdc: Multivariate Distributions Constructed from Copulas

Description

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

Usage

mvdc(copula, margins, paramMargins, marginsIdentical = FALSE,
     check = TRUE, fixupNames = TRUE)
dMvdc(x, mvdc, log=FALSE)
pMvdc(x, mvdc)
rMvdc(n, mvdc)

Arguments

copula

an object of "copula".

margins

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

paramMargins

a list whose each component is a list (or numeric vectors) of named components, giving the parameter values of the marginal distributions. See details below.

marginsIdentical

logical variable restricting the marginal distributions to be identical.

check

logical indicating to apply quick checks about existence of margins p* and d* functions.

fixupNames

logical indicating if the parameters of the margins should get automatic names (from formals(p)).

mvdc

a "mvdc" object.

x

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

log

logical indicating if the log density should be returned.

n

number of observations to be generated.

Value

• mvdc() constructs an object of class "mvdc". dMvdc() gives the density, pMvdc() gives the cumulative distribution function, and rMvdc() generates random variates.

Details

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

A user-defined distribution, for example, fancy, can be used as margin provided that dfancy, pfancy, and qfancy are available.

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

See Also

ellipCopula, archmCopula; the classes mvdc and copula.

Examples

## construct a bivariate distribution whose marginals
## are normal and exponential respectively, coupled
## together via a normal copula
mv.NE <- mvdc(normalCopula(0.75), c("norm", "exp"),
              list(list(mean = 0, sd =2), list(rate = 2)))
dim(mv.NE)
mv.NE  # using its print() / show() method

# Generate (bivariate) random numbers from that, and visualize
x.samp <- rMvdc(100, mv.NE)
plot(x.samp)
dMvdc(x.samp, mv.NE)
pMvdc(x.samp, mv.NE)
persp  (mv.NE, dMvdc, xlim = c(-4, 4), ylim=c(0, 1), main = "dMvdc(mv.NE)")
persp  (mv.NE, pMvdc, xlim = c(-4, 4), ylim=c(0, 1), main = "pMvdc(mv.NE)")
contour(mv.NE, dMvdc, xlim = c(-4, 4), ylim=c(0, 1))