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Estimation of the two-parameter generalized Poisson distribution (GP-1 parameterization) which has the variance as a linear function of the mean.
genpoisson1(lmeanpar = "loglink", ldispind = "logloglink",
imeanpar = NULL, idispind = NULL, imethod = c(1, 1),
ishrinkage = 0.95, gdispind = exp(1:5),
parallel = FALSE, zero = "dispind")
Parameter link functions for Links
for more choices.
In theory the
Optional initial values for
See CommonVGAMffArguments
for information.
The argument is recycled to length 2, and the first value
corresponds to
See CommonVGAMffArguments
for information.
See CommonVGAMffArguments
for information.
Argument gdispind
is similar to gsigma
there and is currently used only if imethod[2] = 2
.
An object of class "vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.
See genpoisson0
for warnings relevant here,
e.g., it is a good idea to monitor convergence because of
equidispersion and underdispersion.
This is a variant of the generalized Poisson distribution (GPD)
and is similar to the
GP-1 referred to by some writers such as Yang, et al. (2009).
Compared to the original GP-0 (see genpoisson0
the GP-1 has
This family function can handle
only overdispersion relative to the Poisson.
An ordinary Poisson distribution corresponds
to
Genpois1
,
genpoisson0
,
genpoisson2
,
poissonff
,
negbinomial
,
Poisson
,
quasipoisson
.
# NOT RUN {
gdata <- data.frame(x2 = runif(nn <- 500))
gdata <- transform(gdata, y1 = rgenpois1(nn, mean = exp(2 + x2),
logloglink(-1, inverse = TRUE)))
gfit1 <- vglm(y1 ~ x2, genpoisson1, data = gdata, trace = TRUE)
coef(gfit1, matrix = TRUE)
summary(gfit1)
# }
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