Abstract This paper starts with a short review of previous work on robust discriminant analysis with emphasis on the projection pursuit approach. Some theoretical aspects are briefly discussed. The core of the paper deals with practical issues related to the projection pursuit approach which gen-eralizes Fisher’s linear discriminant analysis. The choices of univariate es-timators, starting points and maximization procedure are discussed and exemplified. The results of a simulation study are presented.
This thesis is focused on classification methods and their robust alternatives. First, we recall the...
We explore the properties of projection pursuit discriminant analysis. This discriminant method is v...
Strong consistency of linear discriminant analysis is established under wide assumptions on the clas...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
Two projection indices are proposed for the construction of robust 2-sample linear discriminant func...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
Abstract: Linear discriminant analysis is typically carried out using Fisher’s method. This method r...
Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on ...
Linear Discriminant Analysis (LDA) might be the most widely used linear feature extraction method in...
We study the estimation of the linear discriminant with projection pursuit, a method that is unsuper...
This thesis was developed bearing in mind two main purposes: first, the assessment, from a robust vi...
Linear discriminant analysis for multiple groups is typically carried out using Fisher's method. Thi...
Robust linear discriminant analysis for multiple groups: influence and classification efficiencies C...
Fisher's linear discriminant (FLD) is one of the most widely used linear feature extraction met...
This paper aims at comparing the concept of data depth to classification and classification by proje...
This thesis is focused on classification methods and their robust alternatives. First, we recall the...
We explore the properties of projection pursuit discriminant analysis. This discriminant method is v...
Strong consistency of linear discriminant analysis is established under wide assumptions on the clas...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
Two projection indices are proposed for the construction of robust 2-sample linear discriminant func...
AbstractDiscriminant analysis plays an important role in multivariate statistics as a prediction and...
Abstract: Linear discriminant analysis is typically carried out using Fisher’s method. This method r...
Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on ...
Linear Discriminant Analysis (LDA) might be the most widely used linear feature extraction method in...
We study the estimation of the linear discriminant with projection pursuit, a method that is unsuper...
This thesis was developed bearing in mind two main purposes: first, the assessment, from a robust vi...
Linear discriminant analysis for multiple groups is typically carried out using Fisher's method. Thi...
Robust linear discriminant analysis for multiple groups: influence and classification efficiencies C...
Fisher's linear discriminant (FLD) is one of the most widely used linear feature extraction met...
This paper aims at comparing the concept of data depth to classification and classification by proje...
This thesis is focused on classification methods and their robust alternatives. First, we recall the...
We explore the properties of projection pursuit discriminant analysis. This discriminant method is v...
Strong consistency of linear discriminant analysis is established under wide assumptions on the clas...