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.
Results
Showing 1 to 20 of 93 for “"Spatial Models"”.
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Non-Parametric Spatial Models
<p>Covariance functions play a central role in spatial statistics. Parametric covariance functions have been used in most of the existing works on the analysis of spatial data. The primary reason for this is that the classes of parametric covariance functions guarantee that the fitted covariance …
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Essays on testing spatial models
… multiplier (LM) tests) for different types of spatial models. The models studied in this thesis include a spatial dynamic panel data (SDPD) model and a nonlinear SAR (NSAR) model. The proposed test is aiming to solve model selection problems. Chapter 1,""Robust LM tests for spatial dynamic …
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The values of urban design - spatial models
… combinations of transport network encoding and spatial models of distance to evaluate the values of transport network configuration. The commentary critically contextualises the publications’ original contributions with reference to a leading research question and a sub-question: How well does …
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Human mobility and spatial models for infectious disease
… mobility is an important determinant for the spatial spread of human infectious diseases such as influenza but obtaining human mobility datasets has historically been difficult. This thesis investigates two ways to represent human mobility in spatial metapopulation models for the spread of …
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Applications of Spatial Models to Ecology and Social Systems
… landscapes. In this thesis, we study three spatial models arising from from ecology and social sciences. First, in a model introduced by Schelling in 1971, in which families move if they have too many neighbors of the opposite type, we study the phase transition between a randomly …
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Spatial models of metapopulations and benthic communities in patchy environments
… has become a major research focus. These models have been used to explore a wide range of questions concerning population, metapopulation, community, and landscape ecology, in both terrestrial and aquatic systems. In this dissertation I develop and analyze a series of spatial models to …
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Bayesian spatial models for adjusting nonresponse in small area estimation
… approaches. We build generalized linear mixed models in a Bayesian hierarchical spatial modeling framework to estimate response rates and conditional satisfaction rates given response or nonresponse simultaneously at sub-domain level. One model also includes auxiliary information such as hunter …
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Spatial models of Hawaiian streams and Hawaiian stream fish habital
A series of spatially based models of Hawaiian streams and stream fish habitats were developed to aid in the conservation of native fishes. The spatial models focused on the quantification of habitat for native fishes at three levels within a spatial hierarchy. First, at the reach level, the models …
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Dynamics in Discrete Time: Successional Communities, Spatial Models, and Allee Effects
… factors is of particular relevance. Mathematical models can help analyze such population behavior, and their predictions can aid decision-making regarding species conservation, habitat design, biological control, and other matters related to ecosystem management. In this dissertation, I build and …
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Markov chain Monte Carlo methodoloy for inference with generalised linear spatial models
Many real world phenomena are described through models that include an unobserved process which is usually characterised by a continuous distribution. Such models are widely used in geostatistics where a continuous spatial phenomenon is modelled through an underlying latent Gaussian process. If the …
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Development and assessment of predictive spatial models for a rare Tennessee anuran: Barking treefrog (Hyla gratiosa)
… using the program MaxEnt provided results for models that guided field sampling to potential presence locations. From April-August 2017, 126 sites (63 historical; 63 predicted) were visited monthly and sampled for frog calls according to a standardized protocol. Field results revealed H. …
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Spatial Models of Animal Disease Control in South America: The Case of Foot -and -Mouth Disease
This research presents three complementary models of FMD control. The first model is a spatially sensitive epidemiological representation of disease spread. The second model is integrated with the first model to determine the short and long run regional and aggregate costs and benefits of …
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Bayesian Methodology for Missing Data, Model Selection and Hierarchical Spatial Models with Application to Ecological Data
… with many problems such as Missing Data and Spatial Correlation. In this dissertation we use a data set collected by the Ohio EPA as motivation for studying techniques to address these problems. The data set is concerned with the benthic health of Ohio's waterways. A new method for …
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A preliminary study on path planning and obstacle avoidance for construction equipment based on real-time spatial models
… planning, based on real-time three dimensional spatial modeling, have the potential not only to obviate collisions between heavy equipment and other on-site objects, but also to allow autonomous heavy equipment to move to target positions quickly without any accidents. Therefore, algorithms for …
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Spatial models of plant diversity and plant functional traits : towards a better understanding of plant community dynamics in fragmented landscapes
… conditions. All questions were addressed using spatially explicit simulations or statistical models. In chapter 2, I addressed scale-dependent relationships between dispersal capability and species diversity using a grid-based neutral model. I found that the ratio of survey area to landscape …
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Use of spatial models and the MCMC method for investigating the relationship between road traffic pollution and asthma amongst children
… an indicator of road traffic pollution. Also, a spatially driven logistic regression model of the risk of asthma occurrence is developed. The relationship between asthma and pollution is tested using this model. The power of the test has been studied. Because of the uncertainty of exact spatial …
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A Bayesian approach to discovery of latent dependency in point-referenced data
In spatial statistics where data usually was observed as point-referenced, classical and parametric spatial models were assumed and used to describe real-world phenomena. This is generally due to the large number of spatial locations that the spatial models should cover. However, such classical …
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Machine learning analytics for predictive breeding
… data and by the use of appropriate analytic models in the training sets. This research focuses on the impact of data quality for ordinal traits. Ordinal scores of traits are typical for various types of stress tolerance and resistance. Established spatial models developed for continuous …
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Three Essays on the Spatial Autoregressive Model in Spatial Econometrics
The spatial autoregressive model (SAR) is a standard tool to analyze spatial data. It is of great interest in econometrics because it has a game structure and, therefore, can be interpreted as a reaction function: the outcome or behavior of observations at one location is directly affected by those …
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Stochastic models for epidemics on networks
… and reviewed previously solved stochastic spatial models to understand how to solve the multiple-population Reed-Frost model on a network.
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