cluster variables

cluster variables

[¦kləs·tər ¦ver·ē·ə·bəlz]
(astronomy)
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It is bad news that the cluster variables that separate universal and retail banks need to be refined because their low match result implies that discriminatory power is not very high.
Two of the cluster variables switched sign, reputation and access to specialised suppliers, but were a long way from being significant.
More specifically, they provide an explicit geometrical interpretation for the cluster variables in any cluster algebra (of geometric type) whose exchange matrix can be associated with a triangulated surface.
As a possible solution, statistical methods such as PC analysis are applied in order to construct artificial cluster variables determined by the implicit weights of a set of microeconomic indicators.
RR Lyraes are abundant in globular clusters--so much so that they used to be called "cluster variables."
The signs of the coefficients of cluster variables are as expected, even it it is difficult to compare trends of magnitudes of coefficients.
Cluster algebras, introduced by Fomin and Zelevinsky in the early 2000's [10], are a class of commutative rings equipped with a distinguished set of generators (cluster variables) that are grouped into sets of constant cardinality n (the clusters).
As a result, the cluster analysis will first create "clusters" with only the duplicate observations because they have the same values on all cluster variables. This is equivalent as giving them a weight, and it is no longer likely that the largest cities will be put together in the same cluster.
To determine the conceptual model of measuring innovation for competitiveness (ex post) based on the design of cluster variables (CDV), which allows the managers of these companies to recognize, evaluate, decide, and implement actions that transform such organizations to be competitive, the study concluded:
Any cluster algebra comes equipped with a distinguished set of generators called cluster variables which are grouped into finite overlapping subsets called clusters, all of which have the same cardinality.
Data for the cluster variables were compiled from the U.S.
Cluster analysis leads to the formation of maximally homogeneous types that are maximally distinct from all other types on the cluster variables. This is an appropriate statistical analysis for identifying types.