Within Groups Multiple Comparisons Based On Robust Measures Of Location

Within Groups Multiple Comparisons Based On Robust Measures Of Location

Robust Location Based Partial Correlation Robust Location Based Partial Correlation

The visual correspondence problem is a major issue in computer vision. Correlation is a common tool for this problem. Most classical correlation methods fail near the disparity discontinuities, which occur at the boundaries of objects. In this paper, a partial correlation technique is proposed to solve this problem. Robust location methods are used to perform this partial correlation. Compariso...

Within Groups ANOVA When Using a Robust Multivariate Measure of Location

Let θ1, . . . , θJ be measures of location associated with J dependent groups. Various methods have been proposed that are aimed at testing the global hypothesis H0: θ1 = · · · = θJ based on a robust measure of location applied to the marginal distributions. An alternative approach to comparing dependent groups is in terms of difference scores. Let Xij (i = 1, . . . , n; j = 1, . . . , J) be a ...

Interestingness Measures for Association Rules within Groups

The study of association rules within groups of individuals in a database is interesting to define their characteristics and their behavior. In this paper, we define group association rules and we study interestingness measures for them. These evaluation measures can be used to rank groups of individuals and also rules within each group.

Robust uncapacitated multiple allocation hub location problem under demand uncertainty: minimization of cost deviations

The hub location–allocation problem under uncertainty is a real-world task arising in the areas such as public and freight transportation and telecommunication systems. In many applications, the demand is considered as inexact because of the forecasting inaccuracies or human’s unpredictability. This study addresses the robust uncapacitated multiple allocation hub location problem with a set of ...