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In the mentioned studies, the general framework for multivariate problems in which data are collected from a combined array has been presented.
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Outlier detection in multivariate problems is not simple to understand; to describe this problem, simple visual methods can be applied.
Recently, an extension to separable multivariate problems has been given; in this context, the authors have found a matrix representation of the quantum angular momentum, yielding the precise eigenvalues and finite-dimensional vectors that coincide exactly with the spherical harmonics evaluated at a certain set of points.
It has been shown that junction tree algorithms can provide a quick and efficient method for propagating probabilities in complex multivariate problems when they can be described by a fixed conditional independence structure.
The applicability of this approach in a high dimensional multivariate problem is also discussed.
In conclusion, community safety is a multivariate problem that will require a comprehensive solution involving land use planning, fire-safe construction, and property maintenance.
In this paper we present a general framework for the multivariate problem when data are collected from a combined array.
The vegetation cryoturbation interaction was studied across three altitudinal zones by applying hierarchical partitioning (HP) and variation partitioning (VP) methods that overcome collinearity problems in multivariate analysis.
Variance inflation factors were computed for independent variables to identify collinearity problems in multivariate modeling.
Maternal reports of poor behaviour control, combined with poor family cohesion, also increased the likelihood of child Externalising problems in multivariate analysis.
One study found that levels of somatization uniquely predicted adherence problems in a multivariate model [ 109].
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