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W Function: A New Distance‐Based Measure of Spatial Distribution of Economic Activities
Author(s) -
Kukuliač Pavel,
Horák Jiří
Publication year - 2017
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/gean.12120
Subject(s) - measure (data warehouse) , function (biology) , monte carlo method , distribution function , computer science , distribution (mathematics) , dispersion (optics) , statistical physics , probability density function , econometrics , spatial distribution , statistics , mathematical optimization , mathematics , data mining , mathematical analysis , physics , optics , quantum mechanics , evolutionary biology , biology
Distance‐based methods are applied in various fields of research. In this paper, a new relative distance‐based method, the W function, is introduced. This method contributes to the assessment of spatial patterns of economic activities using the stochastic Monte Carlo simulation, and supplements the typology of distance‐based methods recently drawn up by Marcon and Puech. The capability of the W function is compared with results from the Kd and the recently defined m function methods, which are widely used for monitoring the spatial distribution of economic activities by considering several theoretical and empirical examples. The W function appears to provide more precise estimations of the density of economic activities compared to the m and Kd functions, particularly in cases of complex patterns such as double clustered distribution. It also appears to provide a more accurate evaluation of dispersion.