Approximation uses simple linear regression to determine whether
the _location information_ is significant enough (through the
calculated steepness `beta`) which can be used to determine in a
faster and more efficient way whether the calculation of the
model is necessary and helpful in the first place.
The final API will be derived from these scripts into a different
repository, which then only holds the corresponding functions that
provide the corresponding functionalities described in the associated
master thesis.
Model assumes that top 10% of centrality values are not effected by the boundary.
This means that they form the basis for the constant part of the two-part function:
- linear function determined through simple linear regression for the remaining
points that are below the calculated threshold
- constant consistenting of the threshold
The threshold describes the median of the centrality values of the top 10% of the
values.
