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Outlier detection in multivariate problems is not simple to understand; to describe this problem, simple visual methods can be applied.
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The applicability of this approach in a high dimensional multivariate problem is also discussed.
Utilizing RSM and ANN modeling process, linear and nonlinear multivariate regression problems are solved.
Complex multivariate engineering problems are commonplace and not unique to protein engineering.
The method of sequential updates corresponds to the coordinate descent method where multivariate optimization problem is solved by solving a sequence of scalar subproblems, each operating on a selected coordinate (scheduler) while all other coordinates are fixed.
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.
Our data confirm the same synergistic effect of these systems on PCS since, in our multivariate model, cardiac problems are not significant, respiratory problems only approach significance and their interaction is highly significant i.e. their combined effect decreases more the PCS than the sum of the independent negative effect of each condition.
The idea of the multivariate nonparametric Behrens Fisher problem is extended to clustered data and to factorial designs.
Problems are often multivariate or spatial in nature, where interest lies in the risk associated with joint occurrences of rare events, e.g. the risk to multiple offshore structures from a storm event.
Although there was no association with chronological age in this study, multivariate analyses showed that several ageing-related problems were associated with psychosocial problems.
The number with liver problems was too small to have sufficient power in the reported multivariate analysis.
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