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. 2013 Jun 24;8(6):e66341. doi: 10.1371/journal.pone.0066341

Figure 1. Gaussian process regression transforms noisy, irregular, and sparse observations to a longitudinal probability distribution.

Figure 1

A cross section at any point in time in these plots is a proper Gaussian probability density centered at posterior mean Inline graphic with standard deviation Inline graphic. The top panel is a selected leukemia sequence, the bottom panel a selected gout sequence. Black dots: observed values. Dark blue line: posterior mean Inline graphic. Light blue lines: standard deviation Inline graphic.