gammaRob(data, estim = c("tdmean", "M"), save.data = T, control = gammaRob.control(estim, ...), ...)
lognormRob(data, estim = c("tdmean"), save.data = T, control = lognormRob.control(estim, ...), ...)
weibullRob(data, estim = c("tdmean", "M"), save.data = T, control = weibullRob.control(estim, ...), ...)
an asymmetric.dstn object with class "gammaRob", "lognormRob", or "weibullRob" (respectively) containing the following components.
data = T
.
The following elements are included for "tdmean" estimates.
The following element is included for "M" estimates.
The classes "gammaRob", "lognormRob", and "weibullRob" are subclasses of "asymmetric.dstn". The generic methods are defined for class "asymmetric.dstn".
Marazzi A., Ruffieux C. (1999).
The truncated mean of an asymmetric distribution.
Computational Statististic and Data Analysis, 32, pp. 79-100.
Hampel F.R., Ronchetti E.M., Rousseeuw P.J., Stahel W.A. (1986).
Robust statistics: the approach based on influence functions.
Wiley, New York.
Marazzi A., Ruffieux C. (1996).
Implementing M-estimators of the Gamma distribution.
In: Rieder H. (Ed.), Robust Statistics, Data Analysis, and Computer
intensive Methods, Springer Verlag.
los.gammarob <- gammaRob(los)
los.lognormrob <- lognormRob(los)
los.weibullrob <- weibullRob(los)