Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes
Metadatos
Mostrar el registro completo del ítemEditorial
MDPI
Materia
Complexity Divergence Entropy Information transfer Spatial log-Gaussian Cox process
Fecha
2021Referencia bibliográfica
Medialdea, A.; Angulo, J.M.; Mateu, J. Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes. Entropy 2021, 23, 1135. https://doi.org/ 10.3390/e23091135
Patrocinador
MCIU/AEI/ERDF, UE grant PGC2018-098860-B-I00; A-FQM-345-UGR18 - ERDF Operational Programme 2014-2020 and the Economy and Knowledge Council of the Regional Government of Andalusia, Spain; PID2019- 107392RB-I00/AEI/10.13039/501100011033 from the Spanish Ministry of Science and Innovation; UJI-B2018-04 from University Jaume IResumen
The doubly stochastic mechanism generating the realizations of spatial log-Gaussian
Cox processes is empirically assessed in terms of generalized entropy, divergence and complexity
measures. The aim is to characterize the contribution to stochasticity from the two phases involved,
in relation to the transfer of information from the intensity field to the resulting point pattern, as
well as regarding their marginal random structure. A number of scenarios are explored regarding
the Matérn model for the covariance of the underlying log-intensity random field. Sensitivity with
respect to varying values of the model parameters, as well as of the deformation parameters involved
in the generalized informational measures, is analyzed on the basis of regular lattice partitionings.
Both a marginal global assessment based on entropy and complexity measures, and a joint local
assessment based on divergence and relative complexity measures, are addressed. A Poisson process
and a log-Gaussian Cox process with white noise intensity, the first providing an upper bound for
entropy, are considered as reference cases. Differences regarding the transfer of structural information
from the intensity field to the subsequently generated point patterns, reflected by entropy, divergence
and complexity estimates, are discussed according to the specifications considered. In particular,
the magnitude of the decrease in marginal entropy estimates between the intensity random fields
and the corresponding point patterns quantitatively discriminates the global effect of the additional
source of variability involved in the second phase of the double stochasticity.