Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data
Fig 10
ABC interpretation of filter inference.
The figure shows the accepted means and variances of the Gaussian filter at t = 0.6 from the inference results in Fig 4, where filter inference is performed on datasets with 90, 270, 810 and 2430 snapshot measurements of the cancer growth model. The accepted summary statistics are illustrated as black scatter points with the corresponding KDE plots shown in blue. The summary statistics of each dataset is illustrated by a red scatter point. The sample variation of the dataset summary statistics is represented by the 5th to 95th percentile of the summary statistic distribution (red bars), estimated from 1000 realisations of each dataset. The exact mean and variance of the data-generating distribution is close to the intersection of the bars.