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 20 of 38 for “"Geographically Weighted Regression"”.
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Geographically weighted regression and an extension
Includes abstract. Includes bibliographical references (leaves [72]-75).
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Geographically weighted Regression with non-Euclidean distance metrics
Available with hard copy only.
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Spatial Data Analysis
… modeling spatial data; various types of spatial regression techniques, such as Simultaneous Autoregressive (SAR), Conditional Autoregressive (CAR), Generalized Least Squares (GLS), Linear Mixed Effects (LME), and Geographically Weighted Regression (GWR) were discussed. Comparative studies of …
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Concentration and dispersion of primary care physicians and implications for access to care in Cook County, Illinois: 2000-2008
… dispersion of primary care physician locations. Geographically weighted regression models are then used to compare primary care physician supply to the socioeconomic demographics of census tracts in Cook County. Results indicate that spatial clustering of primary care physicians increased over …
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Essays in Economic Geography: Convergence, Inequalities and Innovations in the Knowledge Economy
… heterogeneity in the model. Based on that, a Geographically Weighted Regression approach is used to evaluate the space-varying coefficients."
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A spatial analysis of corn and soybean yields and weather relations
… including two fixed effect models and one geographically weighted regression. Due to different underlying assumptions and specifications of each model, results indicated different implications. Major findings included severe weather conditions during plant.s reproductive stage had much …
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Artificial Intelligence and Spatial Modeling to Estimate Traffic Volume Measures on Local Roadways
… over both the non-spatial RF and conventional Geographically Weighted Regression (GWR) models. Key predictors influencing traffic volume include regional centrality, transit ridership, and employment-residential balance. The results reveal complex, context-dependent relationships, emphasizing …
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Choosing success? Inequalities and opportunities in access to school choice in nine United States districts
… school districts in the U.S. In addition, Geographically Weighted Regression –GWR- analysis is used to assess whether the relation between school choice accessibility and school characteristics vary across all public schools in the U.S. Results from the analysis point to the spatial …
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Spatial Patterns and Variations of Tornado Damage as Related to Southeastern Appalachian Forests and Terrain from the Franklin County, Virginia EF-3 Tornado
… aspect, elevation, and exposure), and 3) Use regression models to determine if relationships exist among terrain variables along the and forest damage patterns. I generated EVI and NDII vegetation indices from Sentinel-2 imagery and compared the derived damage to the underlying terrain …
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Forecasting the use of new local railway stations and services using GIS
… station sites<br/>anywhere in England and Wales. Geographically Weighted Regression (GWR) has been<br/>used to enhance the performance of these models and to account for local variations in the<br/>effects of explanatory variables on rail demand. Flow level models have been produced<br/>for …
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From Section 8 to Starbucks: The Effects of Gentrification on Affordable Housing in Pittsburgh, Pennsylvania
… the process of gentrification. I use various regression models, including OLS, spatial regression, and geographically weighted regression (GWR) to measure the effect of gentrification on affordable housing for three levels of low-income households. This research shows that gentrification is …
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Integrating AI and GIS for Climate-Driven Malaria Monitoring and Demand-Based Resource Distribution and Supply Optimization in Low Developing Countries
… utilized Spatial Autoregressive Models (SAR), Geographically Weighted Regression (GWR), and Random Forest machine learning (R2 = .86) to analyze transmission dynamics. Key findings reveal that minimum temperature is the strongest predictor of transmission (p < .001), while rainfall acts as a …
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Geographical perspectives on international cooperation and conflict
… design in this dissertation uses spatial regression models to explore the spatial context and the scale at which the politics of UN voting is constructed. Second, previous studies of territorial disputes are revisited through the lens of contextual analysis. Building on theoretical and …
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Advanced data analysis methods to optimize crop management decisions
… agronomic treatments is less understood. Mixed geographically weighted regression models were used to estimate local yield response functions. The methodology was applied to investigate the spatial variability in corn response to nitrogen and seed rates in four cornfields in Illinois, USA. The …
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Understanding Urban Vibrancy and Third Places: A Computational Study of the Social Life of Cities Through Multi-Source Digital Trace Data
… clustering, convolutional neural networks, and geographically weighted regression are employed to analyse how socially meaningful places, mobility patterns, and urban form relate to observed activity levels. The findings demonstrate that incorporating measures of third places and social …
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Landscape patterns and patch dynamics in Hamilton county over a forty year period: applicability to the conservation of the eastern box turtle
… analysis of ordinary least squares (OLS) and geographically weighted regression (GWR) models using core as dependent variable and area, perimeter and mean slope as independent variables. Increasing fragmentation and road density over time is indicated by the landscape metrics for site 2 and 3. …
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Responding to Natural Hazards: The Effects of Disaster on Residential Location Decisions and Health Outcomes
… simultaneous autoregressive estimation and geographically weighted regression. Results show that net in-migration rates are negatively correlated with expected frequency. Moreover, the effects of hazard risk are strongest in the Southern U.S.; a region susceptible to increased hazard …
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A Spatial Analysis of Obesity and Its Associations with the Built and Natural Environment, Physical Inactivity, and Socioeconomic and Demographic Conditions in the United States of America
… including the Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR) to investigate obesity and its spatial associations with environmental, behavioral, socioeconomic, sociodemographic, and population based dynamics at the county level. The results from this …
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Patterns and Pathways of Wetland Sedimentation and Landscape Change in Coastal Louisiana
… delta lobes and chenier plain.</p> <p>I applied geographically weighted regression as a supplement to a traditional regression of geological and anthropogenic factors to further explore patterns of landscape variability. I found that the patterns of interior wetland loss are strongly related to …
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Built Environment and Risk of Obesity in the United States: A Multilevel Modeling Approach
… nationwide BRFSS data, the first study used the Geographically Weighted Regression (GWR) model to analyze the obesity rates at the county level. The model results reveal that overall obesity rates are negatively related to walk score and street connectivity, but positively related to poverty …
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