weibull(lshape = "loge", lscale = "loge",
eshape = list(), escale = list(),
ishape = NULL, iscale = NULL,
nrfs = 1, imethod=1, zero = 2)Links for more choices.earg in Links for general information.zero=NULL means none of them."vglmff" (see vglmff-class).
The object is used by modelling functions such as vglm,
and vgam.cenweibull(). It is currently being written and will use
Surv as input.
It should be released in later versions of If the shape parameter is less than two then misleading inference may
result, e.g., in the summary and vcov of the object.
This lshape = "logoff"
and eshape=list(offset=-2).
Johnson, N. L. and Kotz, S. and Balakrishnan, N. (1994) Continuous Univariate Distributions, 2nd edition, Volume 1, New York: Wiley.
Gupta, R. D. and Kundu, D. (2006) On the comparison of Fisher information of the Weibull and GE distributions, Journal of Statistical Planning and Inference, 136, 3130--3144.
dweibull,
gev,
lognormal,
expexp.# Complete data
x = runif(n <- 1000)
y = rweibull(n, shape=exp(1+x), scale = exp(-0.5))
fit = vglm(y ~ x, weibull, trace=TRUE)
coef(fit, mat=TRUE)
vcov(fit)
summary(fit)Run the code above in your browser using DataLab