Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes
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...
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MDPI AG
2021-08-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/23/9/1135 |
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| author | Adriana Medialdea José Miguel Angulo Jorge Mateu |
| author_facet | Adriana Medialdea José Miguel Angulo Jorge Mateu |
| author_sort | Adriana Medialdea |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T07:42:20Z |
| format | Article |
| id | doaj.art-316781c9fa9b4d30950880d161316ecd |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T07:42:20Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-316781c9fa9b4d30950880d161316ecd2023-11-22T12:57:07ZengMDPI AGEntropy1099-43002021-08-01239113510.3390/e23091135Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox ProcessesAdriana Medialdea0José Miguel Angulo1Jorge Mateu2Department of Statistics and Operations Research, University of Granada, 18071 Granada, SpainDepartment of Statistics and Operations Research, University of Granada, 18071 Granada, SpainDepartment of Mathematics, University Jaume I, 12071 Castellón, SpainThe 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.https://www.mdpi.com/1099-4300/23/9/1135complexitydivergenceentropyinformation transferspatial log-Gaussian Cox process |
| spellingShingle | Adriana Medialdea José Miguel Angulo Jorge Mateu Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes Entropy complexity divergence entropy information transfer spatial log-Gaussian Cox process |
| title | Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes |
| title_full | Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes |
| title_fullStr | Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes |
| title_full_unstemmed | Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes |
| title_short | Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes |
| title_sort | structural complexity and informational transfer in spatial log gaussian cox processes |
| topic | complexity divergence entropy information transfer spatial log-Gaussian Cox process |
| url | https://www.mdpi.com/1099-4300/23/9/1135 |
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