bilogistic4(llocation="identity", lscale="loge",
iloc1=NULL, iscale1=NULL, iloc2=NULL, iscale2=NULL,
method.init=1, zero=NULL)
Links
for more choices.Links
for more choices.method.init
. Assigning values here will override
the argument method.init
.method.init
. Assigning values here will override
the argument method.init
.1
or 2
which
specifies the initialization method. If failure to converge occurs
try the other value."vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
rrvglm
and vgam
.By default, $\eta_1=l_1$, $\eta_2=\log(s_1)$, $\eta_3=l_2$, $\eta_4=\log(s_2)$ are the linear/additive predictors.
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.
logistic
,
rbilogis4
.ymat = rbilogis4(n <- 1000, loc1=5, loc2=7, scale2=exp(1))
plot(ymat)
fit = vglm(ymat ~ 1, fam=bilogistic4, trace=TRUE)
coef(fit, matrix=TRUE)
Coef(fit)
fitted(fit)[1:4,]
vcov(fit)
weights(fit, type="w")[1:4,]
summary(fit)
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