N1poisUC: Linear Model and Poisson Mixed Data Type Distribution

In VGAM: Vector Generalized Linear and Additive Models

Linear Model and Poisson Mixed Data Type Distribution

Description

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

Usage

dN1pois(x1, x2, mean = 0, sd = 1, lambda, apar = 0,
        doff = 5, copula = "gaussian", log = FALSE)
rN1pois(n, mean = 0, sd = 1, lambda, apar = 0,
        doff = 5, copula = "gaussian")

Arguments

x1, x2	vector of quantiles. The valid values of x2 are nonnegative integers.
n	number of observations. Same as rnorm.
copula	See N1poisson.
mean, sd, lambda, apar	See N1poisson.
doff	See N1poisson.
log	Logical. If TRUE then the logarithm is returned.

Details

See N1poisson, the VGAM family functions for estimating the parameter by maximum likelihood estimation, for details.

Value

dN1pois gives the probability density/mass function, rN1pois generates random deviate and returns a two-column matrix.

Author(s)

T. W. Yee

See Also

N1poisson, rnorm, rpois.

Examples

## Not run:  
nn <- 1000; mymu <- 1; sdev <- exp(1)
apar <- rhobitlink(0.4, inverse = TRUE)
lambda <- loglink(1, inverse = TRUE)
mat <- rN1pois(nn, mymu, sdev, lambda, apar)
pndata <- data.frame(y1 = mat[, 1], y2 = mat[, 2])
with(pndata, plot(jitter(y1), jitter(y2), col = 4))

## End(Not run)

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