bigumbelIexp: Gumbel's Type I Bivariate Distribution Family Function

View source: R/family.bivariate.R

bigumbelIexpR Documentation

Gumbel's Type I Bivariate Distribution Family Function

Description

Estimate the association parameter of Gumbel's Type I bivariate distribution by maximum likelihood estimation.

Usage

bigumbelIexp(lapar = "identitylink", iapar = NULL, imethod = 1)

Arguments

lapar

Link function applied to the association parameter alpha. See Links for more choices.

iapar

Numeric. Optional initial value for alpha. By default, an initial value is chosen internally. If a convergence failure occurs try assigning a different value. Assigning a value will override the argument imethod.

imethod

An integer with value 1 or 2 which specifies the initialization method. If failure to converge occurs try the other value, or else specify a value for ia.

Details

The cumulative distribution function is

P(Y1 <= y1, Y2 <= y2) = exp(-y1-y2+alpha*y1*y2) + 1 - exp(-y1) - exp(-y2)

for real alpha. The support of the function is for y1>0 and y2>0. The marginal distributions are an exponential distribution with unit mean.

A variant of Newton-Raphson is used, which only seems to work for an intercept model. It is a very good idea to set trace=TRUE.

Value

An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm and vgam.

Note

The response must be a two-column matrix. Currently, the fitted value is a matrix with two columns and values equal to 1. This is because each marginal distribution corresponds to a exponential distribution with unit mean.

This VGAM family function should be used with caution.

Author(s)

T. W. Yee

References

Gumbel, E. J. (1960). Bivariate Exponential Distributions. Journal of the American Statistical Association, 55, 698–707.

See Also

bifgmexp.

Examples

nn <- 1000
gdata <- data.frame(y1 = rexp(nn), y2 = rexp(nn))
## Not run:  with(gdata, plot(cbind(y1, y2))) 
fit <- vglm(cbind(y1, y2) ~ 1, bigumbelIexp, gdata, trace = TRUE)
coef(fit, matrix = TRUE)
Coef(fit)
head(fitted(fit))

VGAM documentation built on July 6, 2022, 5:05 p.m.