Herein, we propose a Spearman rank correlation-based screening procedure for ultrahigh-dimensional data with censored response cases. The proposed method is model-free without specifying any regression forms of predictors or variables and robust under the unknown monotone transformations these variable predictors. sure-screening rank-consistency properties are established some mild regularity c...

Normalized cross correlation (NCC), Sum of squared differences (SSD), and Sum of absolute differences (SAD) are the linear correlation measures generally used for stereo correspondence. These measures fail to establish the correspondence under nonideal conditions such as specular reflection, occlusion etc. In this paper, the similarity measures for stereo correspondence based on rank correlatio...

A low-rate distributed denial of service (DDoS) attack has the ability to obscure its tra c because it is very similar to legitimate tra c. It can easily evade current detection mechanisms. Rank correlation measures can quantify significant di↵erences between attack tra c and legitimate traffic based on their rank values. In this paper, we use two rank correlation measures, namely, Spearmen Ran...

Rank correlation measures are intended to measure to which extent there is a monotonic association between two observables. While they are mainly designed for ordinal data, they are not ideally suited for noisy numerical data. In order to better account for noisy data, a family of rank correlation measures has previously been introduced that replaces classical ordering relations by fuzzy relati...

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C....

In many networks with distributed operation and self-organization features, acquiring their global topological information is impractical, if feasible at all. Internet protocols drawing on node centrality indices may instead approximate them with their egocentric counterparts, computed out over the nodes’ ego-networks. Surprisingly, however, in router-level topologies the approximative power of...

Pearson’s rank correlation coefficient (r) between the vectors of counts and residual values over all tuples was found to be very close to zero (−0.035). Kendall rank correlation coefficient τ between the ranked lists when (w, q) tuples are ordered by frequency and residual value, was found to be −4.65 × 10−9 . This indicates almost no correlation between counts and residuals. Problem Statement