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In this paper multivariate extensions of the Friedman and Page tests for the comparison of several treatments are introduced.
Due to computational constraints, multivariate extensions of the baseline univariate multifractal framework are, however, still very sparse so far.
A new class of multivariate extensions of probability distributions related to local maxima and extremes for scalar Gaussian processes are considered.
However multivariate extensions of this test have not been designed yet and plant data matrix cannot be performed efficiently or without bias.
There are two proposals for multivariate extensions of BG distributions.
In Section 2 we present some basic properties of the class of the BG distributions and a brief review about two multivariate extensions of the BG distribution.
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The derivation carried out can also serve as an example of multivariate extension of univariate models based on exchangeability.
Whereas the voxel-based morphometry (VBM) approach is a univariate approach that automatically segments brain images into voxelwise measures of GM23, SBM, the multivariate extension of VBM, acquires common morphological features of GM concentration among individuals at the network level and thus provides us with structural networks.
A multivariate extension of (9) is also possible.
It is a multivariate extension of the Pythagorean distance between two points.
The Hotelling (T^2) statistic is the multivariate extension of t values calculated for univariate data.
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