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Filtering this representation through the family of sub σ-algebras generated by the multivariate point process of system components, we consider the innovation gain corresponding to the dynamics of component i.
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Again, using Tanzania injectable contraceptives as an example, the bivariate model overestimates the "true" injectables prevalence rate by 1.8 percentage points; the multivariate model by 1.9 percentage points; and the CYP model by 3.3 percentage points.
The canonical axes scores (position of multivariate points on the canonical axes) were then used to determine correlations of each of the original variables with the canonical axes and to test by permutation whether the correlation was significant.
In 2016, Luo et al. [18] presented the concept of multivariate best proximity point and proved the multivariate best proximity point theorems in metric spaces for N-variables contraction mappings.
By using the multivariate interpolation, the computational time of the solving algorithm is reduced.
However, we adjusted the possible influence of different agents by using the multivariate analysis.
The additional multivariate mass point is positive, large and statistically significant for the three return to work durations.
This can be achieved by drawing a i random samples at each space time grid point from the multivariate normal distribution specified by ( tilde{varvec{m}}_{i} ) and ( {tilde{mathbf{C}}}_{i}^{{mathbf{M}}} ).
The aim of this work is to extend the comparison of survival at multiple time points, using the multivariate permutation approach originally introduced by Pesarin [ 4].
In 2016, Su et al. [17] presented the concept of multivariate fixed point and proved a multivariate fixed point theorem for N-variables contraction mappings which further generalizes Banach contraction mapping principle.
By the definition of the multivariate -adic -integral, we have.
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