| Binormcop {VGAM} | R Documentation |
Gaussian Copula (Bivariate) Distribution
Description
Density, distribution function, and random generation for the (one parameter) bivariate Gaussian copula distribution.
Usage
dbinormcop(x1, x2, rho = 0, log = FALSE)
pbinormcop(q1, q2, rho = 0)
rbinormcop(n, rho = 0)
Arguments
x1, x2, q1, q2 |
vector of quantiles.
The |
n |
number of observations.
Same as |
rho |
the correlation parameter.
Should be in the interval |
log |
Logical.
If |
Details
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.
Value
dbinormcop gives the density,
pbinormcop gives the distribution function, and
rbinormcop generates random deviates (a two-column matrix).
Note
Yettodo: allow x1 and/or x2 to have values 1,
and to allow any values for x1 and/or x2 to be
outside the unit square.
Author(s)
T. W. Yee
See Also
Examples
## 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)
## End(Not run)