Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Spatial point process"”.
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Spatial point process modelling of a biodiverse plant community
… of this thesis addresses the suitability of spatial point processes for the modelling of plant communities with the aim of understanding the mechanisms that sustain biodiversity and allow species coexistence through an analysis of a biodiverse plant community in Western …
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Computationally Efficient Specifications of Spatial Point Process Models and Spatio-Temporal Gaussian Models: Combining Remote Sensing Drivers with Geospatial Disease Case Data to Enhance Geographic Epidemiology
… are evaluated for use in analyzing large complex spatial and spatio-temporal data with the goal of contributing to an interdisciplinary effort of developing an eco-epidemiological model that quantifies the relationship between remotely sensed water quality and the incidence of ALS (Amyotrophic …
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Cross-Spectral Analysis For Spatial Point-Lattice Processes
… relationship between the components of a hybrid process consisting of a spatial point process arid a lattice process using two-dimensional spectral techniques. Simulated spatial point-lattice patterns are used to demonstrate how the different cross-spectral statistics can reveal correlation …
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Approaches to the spatial modelling of cancer incidence and mortality in metropolitan Perth, Western Australia, 1990 -2005
… cancers, using two methodologies: Area-to-Point Poisson (ATP) kriging and fitting an inhomogeneous Poisson process model using the Berman-Turner algorithm. ATP Poisson kriging was used to undertake the analysis on the spatial distribution of cancer rates per 100,000 person-years for Perth …
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Topics in functional data analysis and machine learning predictive inference
… principal component analysis, and prediction of spatially correlated functional data. We develop a general framework and fully nonparametric estimation methods for spatial functional data collected under a geostatistics setting, where locations are sampled from a spatial point process and a …
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Stochastic Point Process Modeling for Engineering Applications
<p>Hawkes model or self-exciting point process model is a branching point process model. The model classifies the dataset of discrete events to background and offspring events. It has been used to study interconnected events in many fields, but relatively little work exists in applying these …
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Fast methods for fitting log-Gaussian Cox process models in ecology.
Log-Gaussian Cox processes (LGCPs) offer a framework for regression-style modelling of point patterns that can accommodate latent effects. These latent effects can be used to account for missing predictors or other sources of clustering that could not be explained by a Poisson process. Such models …
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Quantitative ecology reveals scale-dependent structural processes of the Antarctic benthos through time
… and evolutionary factors across different spatial scales. Depth, temperature, salinity, and sea ice impact community structure at large spatial scales (e.g., > 60 km). Far less is known about the interactions between taxa and environment at smaller scales, particularly due to the …