# biamhcopUC: Ali-Mikhail-Haq Bivariate Distribution In VGAM: Vector Generalized Linear and Additive Models

 Biamhcop R Documentation

## Ali-Mikhail-Haq Bivariate Distribution

### Description

Density, distribution function, and random generation for the (one parameter) bivariate Ali-Mikhail-Haq distribution.

### Usage

``````dbiamhcop(x1, x2, apar, log = FALSE)
pbiamhcop(q1, q2, apar)
rbiamhcop(n, apar)
``````

### Arguments

 `x1, x2, q1, q2` vector of quantiles. `n` number of observations. Same as `runif` `apar` the association parameter. `log` Logical. If `TRUE` then the logarithm is returned.

### Details

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

### Value

`dbiamhcop` gives the density, `pbiamhcop` gives the distribution function, and `rbiamhcop` generates random deviates (a two-column matrix).

### Author(s)

T. W. Yee and C. S. Chee

`biamhcop`.

### Examples

`````` x <- seq(0, 1, len = (N <- 101)); apar <- 0.7
ox <- expand.grid(x, x)
zedd <- dbiamhcop(ox[, 1], ox[, 2], apar = apar)
## Not run:
contour(x, x, matrix(zedd, N, N), col = "blue")
zedd <- pbiamhcop(ox[, 1], ox[, 2], apar = apar)
contour(x, x, matrix(zedd, N, N), col = "blue")

plot(r <- rbiamhcop(n = 1000, 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 documentation built on Sept. 19, 2023, 9:06 a.m.