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Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data

Fig 2

Filters in filter inference.

The figure shows a Gaussian filter, a lognormal filter and a Gaussian KDE filter of the early cancer growth model for S = 100 simulated individuals at time t = 1. Each filter is illustrated by a randomly chosen realisation, illustrated in red, and the 5th to 95th percentile of the filter distribution for different sets of simulated individuals. As a reference, the exact population measurement distribution is illustrated in black.

Fig 2

doi: https://doi.org/10.1371/journal.pcbi.1011135.g002