Gaussian Copula (Bivariate) Distribution
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)
x1, x2, q1, q2 |
vector of quantiles.
The |
n |
number of observations.
Same as |
rho |
the correlation parameter. Should be in the interval (-1,1). |
log |
Logical.
If |
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.
dbinormcop gives the density,
pbinormcop gives the distribution function, and
rbinormcop generates random deviates (a two-column matrix).
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.
T. W. Yee
## 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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.