
Maximum likelihood estimation of the 2-parameter Fisk distribution.
fisk(lscale = "loge", lshape1.a = "loge", iscale = NULL,
ishape1.a = NULL, imethod = 1, lss = TRUE, gscale = exp(-5:5),
gshape1.a = seq(0.75, 4, by = 0.25), probs.y = c(0.25, 0.5, 0.75),
zero = "shape")
See CommonVGAMffArguments
for important information.
Parameter link functions applied to the
(positive) parameters scale
.
See Links
for more choices.
See CommonVGAMffArguments
for information.
For imethod = 2
a good initial value for
iscale
is needed to obtain a good estimate for
the other parameter.
See CommonVGAMffArguments
for information.
See CommonVGAMffArguments
for information.
An object of class "vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.
The 2-parameter Fisk (aka log-logistic) distribution is the 4-parameter
generalized beta II distribution with shape parameter
The Fisk distribution has density
scale
,
and
Kleiber, C. and Kotz, S. (2003) Statistical Size Distributions in Economics and Actuarial Sciences, Hoboken, NJ, USA: Wiley-Interscience.
Fisk
,
genbetaII
,
betaII
,
dagum
,
sinmad
,
inv.lomax
,
lomax
,
paralogistic
,
inv.paralogistic
,
simulate.vlm
.
# NOT RUN {
fdata <- data.frame(y = rfisk(n = 200, shape = exp(1), scale = exp(2)))
fit <- vglm(y ~ 1, fisk(lss = FALSE), data = fdata, trace = TRUE)
fit <- vglm(y ~ 1, fisk(ishape1.a = exp(2)), data = fdata, trace = TRUE)
coef(fit, matrix = TRUE)
Coef(fit)
summary(fit)
# }
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