1.1 --- a/README.mkd	Tue Oct 25 18:54:59 2016 +0200
     1.2 +++ b/README.mkd	Tue Oct 25 22:15:17 2016 +0200
     1.3 @@ -494,12 +494,12 @@
     1.4    closest point in the `ecluster` multiplied by the square root of the count of
     1.5    points in the `ecluster`.
     1.6  
     1.7 -The function interally uses a Monte Carlo simulation to compute the result. The
     1.8 -third parameter (which defaults to 10000) can be used to adjust the number of
     1.9 -samples taken. It is ensured that the penalty is always positive, i.e. results
    1.10 -returned by the `fair_distance` function are always equal to or greater than
    1.11 -the results returned by the `distance` function regardless of stochastic
    1.12 -effects.
    1.13 +The function interally uses numerical integration (Monte Carlo like) to compute
    1.14 +the result. The third parameter (which defaults to 10000) can be used to adjust
    1.15 +the number of samples taken. It is ensured that the penalty is always positive,
    1.16 +i.e. results returned by the `fair_distance` function are always equal to or
    1.17 +greater than the results returned by the `distance` function regardless of
    1.18 +stochastic effects.
    1.19  
    1.20  #### `GeoJSON_to_epoint(jsonb, text)`
    1.21