Problem Statement: There have been many cases in real life where two independent sources have ranked n objects, with the interest focused on agreement in the top rankings. Spearman's rho and Kendall's tau coefficients assigned equal weights to all rankings. As a result, the literature proposed several weighted correlation coefficients with emphasis on the top rankings, including the top-down, w...

Background : Epicardial fat thickness and HBA1C level are usefull independent indicator for metabolic syndrome type 2 diabetus mellitus respectively10,9 .studies on the correlation between epicardial in coronary artery disease limited .Hence we aim to evaluate of acute syndrome. Objective The Target this work was investigate link Methodology 123 patient .Electrocardiogram (ECG), pad measured us...

Structure-toxicity relationships were studied for a set of 67 insecticides by means of multiple linear regression (MLR). The values of log LD50 (lethal dose 50, oral, rat) of the studied compounds were well correlated with the descriptors encoding the chemical structures. Considering the pertinent descriptors, a correlation coefficient of 0.87 (s = 0.42, n = 67) was obtained for the MLR model. ...

In multivariate linear regression, it is often assumed that the response matrix is intrinsically of lower rank. This could be because of the correlation structure among the prediction variables or the coefficient matrix being lower rank. To accommodate both, we propose a reduced rank ridge regression for multivariate linear regression. Specifically, we combine the ridge penalty with the reduced...

Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (i) definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (ii) generation of samples from uncertain analysis inputs, (iii) propagation of sampled inputs through an analysis, (iv) presentation of uncertainty analysis results, and (v) deter...

Abstract: Bivariate (or pairwise) information measures such as mutual information or correlation are heavily used in variable selection and network inference algorithms mainly because they are faster and require fewer samples than multivariate (or multidimensional) strategies. This paper proposes a new relevance measure that aims at improving the detection of relevant variables based on pairwis...

This chapter concerns rank tests for independence of two random variables. A form of locally most powerful test against particular alternative is derived and the most often used variants of this test are mentioned, namely the test of van der Waerden type, Spearman rank correlation coefficient, the quadrant test and the Kendall rank correlation coefficient, a member of non-linear rank statistics...