RT Journal Article
T1 Testing similarity between first-order intensities of spatial point processes. A comparative study
A1 Fuentes-Santos, Isabel
A1 González Manteiga, Wenceslao
A1 Mateu, Jorge
K1 Bootstrap calibration
K1 Conditional intensity
K1 Criminology
K1 Environmental risk
K1 Inhomogeneous point process
K1 Nonparametric inference
AB Testing whether two spatial point processes have the same spatial distribution is an important task that can be addressed from different perspectives.A Kolmogorov-Smirnov test with asymptotic calibration and a Cramer von Mises type test with bootstrap calibration have recently been developed to compare the first-order intensity of two observed patterns. Motivated by common practice in epidemiological studies, we introduce a regression test based on the relative risk function with two alternative bootstrap calibrations.This paper compares the performance of these nonparametric tests through both an intensive simulation study, and the application to wildfire and crime data. The three tests provide good calibrations of the null hypothesis for simulated Poisson and non-Poisson spatial point processes,but the Cramer von Mises and regression tests outperform the costefficient Kolmogorov-Smirnov test in terms of power. In the real data analysis we have seen that the Kolmogorov-Smirnov test does not detect differences between spatial point patterns when dealing with sparse data. In view of these results, it would be preferable using the Cramer von Misesor regression tests despite their higher computational demand.
PB Taylor and Francis
SN 1532-4141, 0361-0918
YR 2023
FD 2023
LK http://hdl.handle.net/10347/33370
UL http://hdl.handle.net/10347/33370
LA eng
NO Fuentes-Santos I., González-Manteiga W., Mateu J. (2023) Testing similarity between first-order intensities of spatial point processes. A comparative study, Communications in Statistics - Simulation and Computation, 52:5, 2210-2230
NO This work has been supported by Projects MTM2016-78917-R and MTM2016-76969-P (AEI/FEDER, UE), grantAICO/2019/198 from Generalitat Valenciana, and IAP network StUDyS grant 3E120297 from the BelgianScience Policy.
DS Minerva
RD 28 abr 2026