Figure 1.

Prediction of curves for the first subject, in simulation setting with n = 200 subjects, J = 2 visits per subject, N = 3,6,9,12 grid points per curve and noise variance σ² = 1. Different columns correspond to different levels of sparsity, with the number of grid points varying from 3 to 12. The first and second rows show predictions of subject/visit specific curves, at visit 1 and 2, respectively. In these subfigures, red solid lines correspond to the true underlying curves, Y_ij(t), and red dots are observed sparse data, Y_ij(t_ijs). The thick black dashed lines are the predictions of curves, ${\widehat{Y}}_{ij}\left(t\right)$, and thin black dashed lines give their 95% pointwise confidence bands. The third row display subject level curves, Z_i(t), and their predictions ${\widehat{Z}}_i\left(t\right)$.