Robust descriptive discriminant analysis for repeated measures data

Discriminant Analysis for Repeated Measures Data: A Review

Discriminant analysis (DA) encompasses procedures for classifying observations into groups (i.e., predictive discriminative analysis) and describing the relative importance of variables for distinguishing amongst groups (i.e., descriptive discriminative analysis). In recent years, a number of developments have occurred in DA procedures for the analysis of data from repeated measures designs. Sp...

Repeated measures discriminant analysis 1 Discriminant Analysis for Repeated Measures Data: Effects of Mean and Covariance Misspecification on Bias and Error in Discriminant Function Coefficients

Word Count: 47 Manuscript Word Count: 4387 Repeated measures discriminant analysis 2

Discriminant Analysis for Repeated Measures Data: Effects of Mean and Covariance Misspecification on Bias and Error in Discriminant Function Coefficients

Robust Fisher Discriminant Analysis

Fisher linear discriminant analysis (LDA) can be sensitive to the problem data. Robust Fisher LDA can systematically alleviate the sensitivity problem by explicitly incorporating a model of data uncertainty in a classification problem and optimizing for the worst-case scenario under this model. The main contribution of this paper is show that with general convex uncertainty models on the proble...

Discriminant analysis for compositional data and robust parameter estimation

Abstract Compositional data, i.e. data including only relative information, need to be transformed prior to applying the standard discriminant analysis methods that are designed for the Euclidean space. Here it is investigated for linear, quadratic, and Fisher discriminant analysis, which of the transformations lead to invariance of the resulting discriminant rules. Moreover, it is shown that f...