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Practical identifiability of HIV dynamics models.

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Academic year: 2021

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Figure

Figure 1. Simulated trajectories for the virus load (left) and the total CD4 counts (right) after antiretroviral treatment initiation when the random  ef-fects and the error measurements are set to be null
Figure 2. 100 simulated trajectories for the virus load (left) and the total CD4 counts (right) The trajectories for the biomarkers share common  fea-tures but may vary between the (simulated) patients since each individual value of α, λ and µ T ∗ are the
Figure 3. Empirical distribution of E D (θ). The dot line corresponds to the result obtained for the central parameter value θ 0 given in Table 3
Table 2: Observed components considered regarding the number of available markers M

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