TY - JOUR
T1 - Effects of missing data and locational errors on spatial concentration measures based on Ripley’s K-function
AU - Arbia, Giuseppe
AU - Espa, Giuseppe
AU - Giuliani, Diego
AU - Dickson, Maria Michela
PY - 2017
Y1 - 2017
N2 - measures based on Ripley's k function are the tools of election to test the concentration of individual agents in the economic space. In many empirical cases, however, the datasets contain differemt inaccuracies due to missing data or to uncertainty about the location of agents. Little is known, so far, on the effects of these inaccuracies on the K-.function. This paper aims at shedding light on on the problem through a theoretical analysis supported by Monte ACrlo experiments. The results show that pattern of Clustering or inhibition may be observed not as genuine phenomena, but only as the effect of data imperfection
AB - measures based on Ripley's k function are the tools of election to test the concentration of individual agents in the economic space. In many empirical cases, however, the datasets contain differemt inaccuracies due to missing data or to uncertainty about the location of agents. Little is known, so far, on the effects of these inaccuracies on the K-.function. This paper aims at shedding light on on the problem through a theoretical analysis supported by Monte ACrlo experiments. The results show that pattern of Clustering or inhibition may be observed not as genuine phenomena, but only as the effect of data imperfection
KW - spatial concentration
KW - spatial concentration
UR - http://hdl.handle.net/10807/116314
U2 - 10.1080/17421772.2017.1297479
DO - 10.1080/17421772.2017.1297479
M3 - Article
SN - 1742-1772
VL - 12
SP - 326
EP - 346
JO - Spatial Economic Analysis
JF - Spatial Economic Analysis
ER -