Fine-tuning the method

[philiprn]

Our method involves the superposition of a series of Gaussian 'bumps' which are centred on top of the fitted positions. To do so, we smooth each position separately and keep it in memory as a density histogram.

However, this is mathematically very similar to kernel density estimation and the use of radial basis or weight functions, which does not require to build separate histograms. We have to check whether using one implementation or the other has any effect on the results, as this choice might influence the amount of truncation and approximation introduced in the statistical modelling, and thus the accuracy.