We define an asymptotic mean version of Tukey's sensitivity curve. For this we show that some of the more important features of Hampel's influence function hold for L- and M-estimators also. Therefore, we have an alternative approach to the influence function using only expectations and limits.Influence function Sensitivity curve L-estimator M-estimator
Influence curves for the initial and rotated loadings are derived for the maximum likelihood factor ...
Influence functions are useful, for example, because they provide an easy and flexible way to estima...
The empirical influence function EIF(x,T-n;X) measures the influence of an observation x on the esti...
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
There are many economic parameters that depend on nonparametric first steps. Examples include games,...
The influencecurve (JC) of a Fisher-consistent functional was introduced by F. Hampel and plays a ce...
We investigate optimal bounded influence M-estimators in the general normal regression model with re...
AbstractIn this paper we extend the definition of the influence function to functionals of more than...
Often semiparametric estimators are asymptotically equivalent to a sample average. The object being ...
Influence functions for L-estimates are estimated and a weak approximation in terms of Gaussian proc...
AbstractWe investigate optimal bounded influence M-estimators in the general normal regression model...
We prove the asymptotic validity of bootstrap confidence bands for the influence curve from its usua...
The case sensitivity function approach to influence analysis is introduced as a natural smooth exten...
<p>The influence function for the first component of the minimum pseudodistance estimator of the mea...
The notion of influence function was introduced by Hampel and it plays a crucial role for the impor...
Influence curves for the initial and rotated loadings are derived for the maximum likelihood factor ...
Influence functions are useful, for example, because they provide an easy and flexible way to estima...
The empirical influence function EIF(x,T-n;X) measures the influence of an observation x on the esti...
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
There are many economic parameters that depend on nonparametric first steps. Examples include games,...
The influencecurve (JC) of a Fisher-consistent functional was introduced by F. Hampel and plays a ce...
We investigate optimal bounded influence M-estimators in the general normal regression model with re...
AbstractIn this paper we extend the definition of the influence function to functionals of more than...
Often semiparametric estimators are asymptotically equivalent to a sample average. The object being ...
Influence functions for L-estimates are estimated and a weak approximation in terms of Gaussian proc...
AbstractWe investigate optimal bounded influence M-estimators in the general normal regression model...
We prove the asymptotic validity of bootstrap confidence bands for the influence curve from its usua...
The case sensitivity function approach to influence analysis is introduced as a natural smooth exten...
<p>The influence function for the first component of the minimum pseudodistance estimator of the mea...
The notion of influence function was introduced by Hampel and it plays a crucial role for the impor...
Influence curves for the initial and rotated loadings are derived for the maximum likelihood factor ...
Influence functions are useful, for example, because they provide an easy and flexible way to estima...
The empirical influence function EIF(x,T-n;X) measures the influence of an observation x on the esti...