Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

bifgmcopUC

Farlie-Gumbel-Morgenstern's Bivariate Distribution


Description

Density, distribution function, and random generation for the (one parameter) bivariate Farlie-Gumbel-Morgenstern's distribution.

Usage

dbifgmcop(x1, x2, apar, log = FALSE)
pbifgmcop(q1, q2, apar)
rbifgmcop(n, apar)

Arguments

x1, x2, q1, q2

vector of quantiles.

n

number of observations. Same as in runif.

apar

the association parameter.

log

Logical. If TRUE then the logarithm is returned.

Details

See bifgmcop, the VGAM family functions for estimating the parameter by maximum likelihood estimation, for the formula of the cumulative distribution function and other details.

Value

dbifgmcop gives the density, pbifgmcop gives the distribution function, and rbifgmcop generates random deviates (a two-column matrix).

Author(s)

T. W. Yee

See Also

Examples

## Not run:  N <- 101; x <- seq(0.0, 1.0, len = N); apar <- 0.7
ox <- expand.grid(x, x)
zedd <- dbifgmcop(ox[, 1], ox[, 2], apar = apar)
contour(x, x, matrix(zedd, N, N), col = "blue")
zedd <- pbifgmcop(ox[, 1], ox[, 2], apar = apar)
contour(x, x, matrix(zedd, N, N), col = "blue")

plot(r <- rbifgmcop(n = 3000, apar = apar), col = "blue")
par(mfrow = c(1, 2))
hist(r[, 1])  # Should be uniform
hist(r[, 2])  # Should be uniform

## End(Not run)

VGAM

Vector Generalized Linear and Additive Models

v1.1-5
GPL-3
Authors
Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)
Initial release
2021-01-13

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.