Classes for bounded, robust, standardized weights.
Objects can be created by calls of the form new("BdStWeight", ...);
to fill slot weight, you will use the generating functions
getweight and minbiasweight.
nameObject of class "character"; inherited from class RobWeight.
weightObject of class "function" --- the weight function; inherited from class RobWeight.
clipObject of class "numeric" --- clipping bound(s); inherited from class BoundedWeight.
standObject of class "matrix" --- standardization.
Class "RobWeight", via class "BoundedWeight".
Class "BoundedWeight", directly.
signature(object = "BdStWeight"):
accessor function for slot stand.
signature(object = "BdStWeight", value = "matrix"):
replacement function for slot stand. This replacement method
should be used with great care, as the slot weight is not
simultaneously updated and hence, this may lead to inconsistent
objects.
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
Hampel et al. (1986) Robust Statistics. The Approach Based on Influence Functions. New York: Wiley.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
BoundedWeight-class, RobWeight-class,
IC, InfluenceCurve-class
## prototype
new("BdStWeight")
Run the code above in your browser using DataLab