AbstractIn this paper we extend the definition of the influence function to functionals of more than one distribution, that is, for estimators depending on more than one sample, such as the pooled variance, the pooled covariance matrix, and the linear discriminant analysis coefficients. In this case the appropriate designation should be “partial influence functions,” following the analogy with derivatives and partial derivatives. Some useful results are derived, such as an asymptotic variance formula. These results are then applied to several estimators of the Mahalanobis distance between two populations and the linear discriminant function coefficients
In this paper, we compute the influence function (IF) for partial least squares (PLS) regression. Th...
We prove the asymptotic validity of bootstrap confidence bands for the influence curve from its usua...
This paper considers the role of influence diagnostics in the partially linear regression models, y ...
AbstractIn this paper we extend the definition of the influence function to functionals of more than...
There are many economic parameters that depend on nonparametric first steps. Examples include games,...
Often semiparametric estimators are asymptotically equivalent to a sample average. The object being ...
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
Influence functions are useful, for example, because they provide an easy and flexible way to estima...
Outliers, from a subjective point of view, are observations which are discordant from the other rema...
The notion of influence function was introduced by Hampel and it plays a crucial role for the impor...
The influencecurve (JC) of a Fisher-consistent functional was introduced by F. Hampel and plays a ce...
We define an asymptotic mean version of Tukey's sensitivity curve. For this we show that some of the...
The influence of a variable is an important concept in the analysis of Boolean functions. The more g...
We propose and analyze estimators for statistical functionals of one or more distributions under non...
Regression specifications in applied econometrics frequently employ regressors that are defined as t...
In this paper, we compute the influence function (IF) for partial least squares (PLS) regression. Th...
We prove the asymptotic validity of bootstrap confidence bands for the influence curve from its usua...
This paper considers the role of influence diagnostics in the partially linear regression models, y ...
AbstractIn this paper we extend the definition of the influence function to functionals of more than...
There are many economic parameters that depend on nonparametric first steps. Examples include games,...
Often semiparametric estimators are asymptotically equivalent to a sample average. The object being ...
AbstractThe influence curve (JC) of a Fisher-consistent functional was introduced by F. Hampel and p...
Influence functions are useful, for example, because they provide an easy and flexible way to estima...
Outliers, from a subjective point of view, are observations which are discordant from the other rema...
The notion of influence function was introduced by Hampel and it plays a crucial role for the impor...
The influencecurve (JC) of a Fisher-consistent functional was introduced by F. Hampel and plays a ce...
We define an asymptotic mean version of Tukey's sensitivity curve. For this we show that some of the...
The influence of a variable is an important concept in the analysis of Boolean functions. The more g...
We propose and analyze estimators for statistical functionals of one or more distributions under non...
Regression specifications in applied econometrics frequently employ regressors that are defined as t...
In this paper, we compute the influence function (IF) for partial least squares (PLS) regression. Th...
We prove the asymptotic validity of bootstrap confidence bands for the influence curve from its usua...
This paper considers the role of influence diagnostics in the partially linear regression models, y ...