Frechet Distribution Family Function
frechet.RdMaximum likelihood estimation of the 2-parameter Frechet distribution.
Usage
frechet(location = 0, lscale = "loglink",
lshape = logofflink(offset = -2),
iscale = NULL, ishape = NULL, nsimEIM = 250, zero = NULL)Arguments
- location
Numeric. Location parameter. It is called \(a\) below.
- lscale, lshape
Link functions for the parameters; see
Linksfor more choices.- iscale, ishape, zero, nsimEIM
See
CommonVGAMffArgumentsfor information.
Details
The (3-parameter) Frechet distribution has a density function that can be written $$f(y) = \frac{sb}{ (y-a)^2} [b/(y-a)]^{s-1} \, \exp[-(b/(y-a))^s] $$ for \(y > a\) and scale parameter \(b > 0\). The positive shape parameter is \(s\). The cumulative distribution function is $$F(y) = \exp[-(b/(y-a))^s]. $$ The mean of \(Y\) is \(a + b \Gamma(1-1/s)\) for \(s > 1\) (these are returned as the fitted values). The variance of \(Y\) is \(b^2 [ \Gamma(1-2/s) - \Gamma^2(1-1/s)]\) for \(s > 2\).
Family frechet has \(a\) known, and
\(\log(b)\) and
\(\log(s - 2)\) are the default
linear/additive predictors.
The working weights are estimated by simulated Fisher scoring.
Value
An object of class "vglmff"
(see vglmff-class).
The object is used by modelling functions such
as vglm
and vgam.
References
Castillo, E., Hadi, A. S., Balakrishnan, N. and Sarabia, J. S. (2005). Extreme Value and Related Models with Applications in Engineering and Science, Hoboken, NJ, USA: Wiley-Interscience.
Warning
Family function frechet may fail for low values of
the shape parameter, e.g., near 2 or lower.
Examples
if (FALSE) { # \dontrun{
set.seed(123)
fdata <- data.frame(y1 = rfrechet(1000, shape = 2 + exp(1)))
with(fdata, hist(y1))
fit2 <- vglm(y1 ~ 1, frechet, data = fdata, trace = TRUE)
coef(fit2, matrix = TRUE)
Coef(fit2)
head(fitted(fit2))
with(fdata, mean(y1))
head(weights(fit2, type = "working"))
vcov(fit2)
} # }