R: Methods for 'plot' in Package 'copula'

plot-methods {copula} | R Documentation

## Methods for 'plot' in Package 'copula'

### Description

Methods for `plot()` to draw a scatter plot of a random sample from bivariate distributions from package copula.

### Usage

    ## S4 method for signature 'Copula,ANY'
    plot(x, n, xlim = 0:1, ylim = 0:1,
          xlab = quote(U[1]), ylab = quote(U[2]), main = NULL, ...)
    ## S4 method for signature 'mvdc,ANY'
    plot(x, n, xlim = NULL, ylim = NULL,
          xlab = quote(X[1]), ylab = quote(X[2]), ...)

### Arguments

`x` | a bivariate `"matrix"`, `"data.frame"`, `"Copula"` or a `"mvdc"` object.
`n` | when `x` is not matrix-like: The sample size of the random sample drawn from `x`.
`xlim, ylim` | the x- and y-axis limits.
`xlab, ylab` | the x- and y-axis labels.
`main` | the main title; when true, shows the call's `x` “expression”. By default, when `NULL` and the `x` expression matches `"[Cc]opula"` that expression is used as well. This smart default is somewhat experimental; feedback is welcome.
`...` | additional arguments passed to `plot` methods, i.e., typically `plot.default`.

### Value

invisible().

### See Also

`splom2()` for a scatter-plot matrix based on `splom()`.

### Examples

    ## For 2-dim. 'copula' objects -------------------------
    ## Plot uses  n  compula samples
    n <- 1000 # sample size
    set.seed(271) # (reproducibility)
    plot(tCopula(-0.8, df = 1.25), n = n) # automatic main title!

    nu <- 3 # degrees of freedom
    tau <- 0.5 # Kendall's tau
    th <- iTau(tCopula(df = nu), tau) # corresponding parameter
    cop <- tCopula(th, df = nu) # define 2-d copula object
    plot(cop, n = n)

    ## For 2-dim. 'mvdc' objects ---------------------------
    mvNN <- mvdc(cop, c("norm", "norm"),
                 list(list(mean = 0, sd = 1), list(mean = 1)))
    plot(mvNN, n = n)

[Package copula version 1.0-1 Index]