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234 bytes added ,  16:15, 8 March 2021
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== Approach ==
 
== Approach ==
In the figure the results for Maroc are shown.
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In the figure the results for the french departments are shown.
[[File:TransportationSizeMaroc.png|thumb|center|The population road-distance weighted transportation size of Maroc]]
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[[File:France transportation size.png|thumb|The population road-distance weighted size of France based on the departments]]
 
The cumulative population road-distance weighted distances are plotted against the cumulative population ratios. Each added city adds a point, increasing the cumulative population ratio and the cumulative distance. If the cumulative population ratio is 1, we have covered the entire population. And the corresponding cumulative distance is the value we are looking for.
 
The cumulative population road-distance weighted distances are plotted against the cumulative population ratios. Each added city adds a point, increasing the cumulative population ratio and the cumulative distance. If the cumulative population ratio is 1, we have covered the entire population. And the corresponding cumulative distance is the value we are looking for.
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* power functions - results in larger values, but goes through (0,0);
 
* power functions - results in larger values, but goes through (0,0);
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In order to get a handle on what is the best function, a plot has been created for the departments in France. With a population fraction of 87%, the power function gives the best fit to the data, using all points.
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The results of France show that the logarithmic function does not fit the data. The best fit is provided by a power functions. However this works only if there is enough data above a population fraction of 25%. The data below 25% heavily influences the outcome of a power functions. As an approximation a linear fit, without using the data at low values gives a better estimate. For France in fact the results are the same.
    
== Result ==
 
== Result ==
3,393

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