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This was explored by Principal Components Analysis with Varimax rotation, (a rotation that minimises the correlation between components).
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The main idea behind the second adopted method is to minimise the correlation between classifier outputs.
This clearly differentiates them to the proposed scheme where the aim is not strictly to minimise the correlation of the spatial streams but rather to optimise it and accommodate for constructive interchannel interference (ICI).
In contrast to orthogonal designs, efficient designs are not intended to minimise the correlation of the data for estimation purposes, but to generate parameter estimates with the lowest possible standard errors [22].
The minimum eigenvalue will be set at 1 and appropriate rotations will be performed to minimise the correlation among factors.
The GINI coefficient was centred (i.e. X = Gini-mean(Gini)) in order to minimise the correlation between coefficients.
As such, they attempt to minimise the correlation in the data for estimation purposes and collect data such that parameter estimates have as small as possible SEs.
As such, they attempt to minimise the correlation in the data for estimation purposes, and collect data such that parameter estimates have as small as possible standard errors.
Hence, the minority choice minimises the average correlation of the colluders.
This is believed to be due, in part, to the ability of the PI arms to drag the small section of polybutadiene into their own territory causing the fluctuation of the interface from the connection point, and which also minimises the monomer correlation near the junction point.
The principle used is the minimisation of the correlation in the data for estimation purposes so that standard errors on parameter estimates are ultimately minimised.
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