Substance contributions to components

The SNMU solution of matrix U can be displayed in a heatmap. The heatmap shows the relative contribution of each substance to a component.

Figure 85 SNMU: matrix \(U\), substance contributions to components.

In Figure 86 and Figure 87 the sparsity parameter is set to 0.1 (not sparse) and 0.8 (sparse), respectively. This leads to components containing different number of substances.

Figure 86 Co-exposure of substances. Heatmap for a solution with 6 components. The sparsity = 0.1. Each component, especially the first, contains many substances (see also Figure 87).

Figure 87 Co-exposure of substances. Heatmap for a solution with 6 components. The sparsity = 0.8. Components contain less substances compared to Figure 86.

In Figure 88, the relative contributions of the substances to the first component are displayed in a piechart.

Figure 88 Relative contributions substances to component 1. The sparsity is set to 0.8 (sparse), estimated sparsity = 0.62.

As mentioned before, one of the nice features of the SNMU algorithm is its recursive character which results in identical components. In Figure 89, the U matrix is visualized using three components. Compare this solution with Figure 87, the first three components are identical. Because of the ordering the plots look slightly different, but a closer inspection of the first 3 components of each solution shows that they are the same. In both figures, component 1 contains mbzp, A, B, C and D; component 2, mibp, E, F and ohmehp; and component 3 mnbp and G.

Figure 89 Heatmap for solution with 3 components. The first 3 components in Figure 89 and Figure 87 contain the same substances.

In paragraph network analysis, an alternative to the SNMU approach is proposed.

For selection of individual(day) exposures with a maximum cumulative ratio above a cutoff and/or above a cutoff percentage in the set of individual(day)s ranked on total exposure, see ‘Cutoff MCR’ and ‘Cutoff percentage’ settings.