N1binomUC: Linear Model and Binomial Mixed Data Type Distribution

In VGAM: Vector Generalized Linear and Additive Models

Linear Model and Binomial Mixed Data Type Distribution

Description

Density, and random generation for the (four parameter bivariate) Linear Model–Bernoulli copula distribution.

Usage

dN1binom(x1, x2, mean = 0, sd = 1, prob, apar = 0,
         copula = "gaussian", log = FALSE)
rN1binom(n, mean = 0, sd = 1, prob,
         apar = 0, copula = "gaussian")

Arguments

x1, x2	vector of quantiles. The valid values of x2 are 0 and 1.
n	number of observations. Same as rnorm.
copula	See N1binomial.
mean, sd, prob, apar	See N1binomial.
log	Logical. If TRUE then the logarithm is returned.

Details

See N1binomial, the VGAM family functions for estimating the parameter by maximum likelihood estimation, for details.

Value

dN1binom gives the probability density/mass function, rN1binom generates random deviate and returns a two-column matrix.

Author(s)

T. W. Yee

See Also

N1binomial, rnorm, rbinom.

Examples

## Not run:  
nn <- 1000;  apar <- rhobitlink(1.5, inverse = TRUE)
prob <- logitlink(0.5, inverse = TRUE)
mymu <- 1; sdev <- exp(1)
mat <- rN1binom(nn, mymu, sdev, prob, apar)
bndata <- data.frame(y1 = mat[, 1], y2 = mat[, 2])
with(bndata, plot(jitter(y1), jitter(y2), col = "blue"))

## End(Not run)

VGAM documentation built on Sept. 18, 2024, 9:09 a.m.