… financial correlation matrices to compare and test the robustness … decreases faster than
intersector correlation between pairs … Reference [51] applies a hierarchical clustering to a set of …

… optimization combined with the powerful toolbox of gradient… (1) Rather than minimizing the
cost function by optimizing … is a fast top-down algorithm that splits the data into two clusters at …

… used to account for correlated or clustered data, especially in … In R, functions for covariances
in clustered or panel models … They are robust against panel heteroscedasticity and contem…

… a hierarchical clustering which allows us to find clusters of … the powerful Extract-ξ method
for grouping points into clusters … Next, we define a function that clusters the data given a set of …

… significantly outperformed hierarchical clustering combination … robustness of the proposed
method for its parameter setting. … the clustering results (consensus function) and produce final …

… separation between clusters and strong population structure … of Ward’s hierarchical clustering
in the fastcluster package (31)… function which accounts for both within-cluster and between-…

… -based method such as hierarchical clustering [33], centroid-… of feature points xi and yi
typically have high correlation. … Note that the precision of our RFM-SCAN drops faster than the …

… used clustering statistic – the two-point correlation function (2PCF). The 2PCF is a powerful
probe of … Typically, we extract cosmological information from the correlation function at ‘large’ …

… Reasonable efforts have been made to publish reliable data and information, but the author
… hierarchically or spatio-temporally correlated effects via conditionally specified hierarchical …

… by providing an object to be associated with a cluster using a membership function. Fuzzy …
to explain ozone spatial distributions, and their correlation to those in the San Francisco Basin …