
Density, distribution function, and random generation for the (one parameter) bivariate Gaussian copula distribution.
dbinormcop(x1, x2, rho = 0, log = FALSE)
pbinormcop(q1, q2, rho = 0)
rbinormcop(n, rho = 0)
vector of quantiles.
The x1
and x2
should be in the interval q1
and q2
.
number of observations.
Same as rnorm
.
the correlation parameter.
Should be in the interval
Logical.
If TRUE
then the logarithm is returned.
dbinormcop
gives the density,
pbinormcop
gives the distribution function, and
rbinormcop
generates random deviates (a two-column matrix).
See binormalcop
, the VGAM
family functions for estimating the
parameter by maximum likelihood estimation,
for the formula of the
cumulative distribution function and other details.
# NOT RUN {
edge <- 0.01 # A small positive value
N <- 101; x <- seq(edge, 1.0 - edge, len = N); Rho <- 0.7
ox <- expand.grid(x, x)
zedd <- dbinormcop(ox[, 1], ox[, 2], rho = Rho, log = TRUE)
contour(x, x, matrix(zedd, N, N), col = "blue", labcex = 1.5)
zedd <- pbinormcop(ox[, 1], ox[, 2], rho = Rho)
contour(x, x, matrix(zedd, N, N), col = "blue", labcex = 1.5)
# }
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