50% off | Unlimited Data & AI Learning

Last chance! 50% off unlimited learning

Sale ends in


VGAM (version 0.7-5)

fgm: Farlie-Gumbel-Morgenstern's Bivariate Distribution Family Function

Description

Estimate the association parameter of Farlie-Gumbel-Morgenstern's bivariate distribution using maximum likelihood estimation.

Usage

fgm(lapar="rhobit", earg=list(), iapar=NULL,
    method.init=1, nsimEIM=200)

Arguments

Value

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

Details

The cumulative distribution function is P(Y1y1,Y2y2)=y1y2(1+α(1y1)(1y2)) for $-1 < \alpha < 1$. The support of the function is the unit square. The marginal distributions are the standard uniform distributions. When $\alpha = 0$ the random variables are independent.

References

Castillo, E., Hadi, A. S., Balakrishnan, N. Sarabia, J. S. (2005) Extreme Value and Related Models with Applications in Engineering and Science, Hoboken, N.J.: Wiley-Interscience.

See Also

rfgm, frank, morgenstern.

Examples

Run this code
ymat = rfgm(n = 1000, alpha=rhobit(3, inverse=TRUE))
plot(ymat, col="blue")
fit = vglm(ymat ~ 1, fam=fgm, trace=TRUE)
coef(fit, matrix=TRUE)
Coef(fit)
fitted(fit)[1:5,]

Run the code above in your browser using DataLab