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. 2010 Oct 7;6(10):e1000949. doi: 10.1371/journal.pcbi.1000949

Figure 3. Computational simulation demonstrates that temporal model can reduce the biases generated by the Type II data (low reactors) in hemagglutination inhibition (HI) dataset.

Figure 3

(a) HI matrix (Inline graphic data absense) with neither Type II nor Type III data, using multidimensional scaling (MDS); (b) HI matrix (Inline graphic data absense, data structure: randomly distributed) with Type III data but without Type II data, using Alternating Gradient Descent (AGD) and MDS; (c) HI matrix (Inline graphic data absense, data structure: similar to H3N2 data as shown in Figure 1) with both Type II data and Type III data, using AGD and MDS; (d)HI matrix (Inline graphic data absense, data structure: similar to H3N2 data as shown in Figure 1) with both Type II and Type III data, using MC-MDS. (e)HI matrix (Inline graphic data absense, data structure: similar to H3N2 data as shown in Figure 1) with both Type II and Type III data, using Metric MDS. (f) Another independent run by the same setting and method as (e).