Last chance! 50% off unlimited learning
Sale ends in
inv.binomial(lrho = extlogit(min = 0.5, max = 1),
llambda = "loge", irho = NULL, ilambda = NULL, zero = NULL)
Links
for more choices."vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
and vgam
.Jain, G. C. and Consul, P. C. (1971) A generalized negative binomial distribution. SIAM Journal on Applied Mathematics, 21, 501--513.
Jorgensen, B. (1997) The Theory of Dispersion Models. London: Chapman & Hall
negbinomial
,
poissonff
.idata <- data.frame(y = rnbinom(n <- 1000, mu = exp(3), size = exp(1)))
fit <- vglm(y ~ 1, inv.binomial, data = idata, trace = TRUE)
with(idata, c(mean(y), head(fitted(fit), 1)))
summary(fit)
coef(fit, matrix = TRUE)
Coef(fit)
sum(weights(fit)) # Sum of the prior weights
sum(weights(fit, type = "work")) # Sum of the working weights
Run the code above in your browser using DataLab