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exppoisson(llambda = "loge", lbetave = "loge",
ilambda = 1.1, ibetave = 2, zero = NULL)
Links
for more choices.lambda
and betave
parameters.
Currently this function is not intelligent enough to
obtain better initial values."vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
and vgam
.hypergeo
package
(to use their genhypergeo
function).dexppois
,
exponential
,
poisson
.lambda = exp(1); betave = exp(2)
rdata = data.frame(y = rexppois(n = 1000, lambda, betave))
library(hypergeo)
fit = vglm(y ~ 1, exppoisson, rdata, trace = TRUE)
c(with(rdata, mean(y)), head(fitted(fit), 1))
coef(fit, matrix = TRUE)
Coef(fit)
summary(fit)
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