levy(delta = NULL, link.gamma = "loge", earg=list(),
idelta = NULL, igamma = NULL)
Links
for more choices.earg
in Links
for general information."vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.nn = 1000; delta = 0
mygamma = 1 # log link ==> 0 is the answer
ldat = data.frame(y = delta + mygamma/rnorm(nn)^2) # Levy(mygamma, delta)
# Cf. Table 1.1 of Nolan for Levy(1,0)
with(ldat, sum(y > 1) / length(y)) # Should be 0.6827
with(ldat, sum(y > 2) / length(y)) # Should be 0.5205
fit = vglm(y ~ 1, levy(delta=delta), ldat, trace=TRUE) # 1 parameter
fit = vglm(y ~ 1, levy(idelta=delta, igamma=mygamma),
ldat, trace=TRUE) # 2 parameters
coef(fit, matrix=TRUE)
Coef(fit)
summary(fit)
head(weights(fit, type="w"))
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