plot-methods | R Documentation |
Methods for plot()
to draw a scatter plot of a random
sample from bivariate distributions from package copula.
## 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]), ...)
x |
a bivariate |
n |
when |
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 |
... |
additional arguments passed to |
invisible().
splom2()
for a scatter-plot matrix based on
splom()
.
## 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)
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