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 18 of 18 for “"Geographically Weighted Regression (GWR)"”.
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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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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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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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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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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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Factors influencing hunting license sales in urban and rural areas of Illinois
… consisted of three parts. The first created a regression model for the entire state. Different socioeconomic and biophysical factors were included in the model. Model was transformed to reduce heteroscedasticity and non-normality. Stepwise regression was applied to the transformed model to …
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EXAMINING THE IMPACT OF NATURE-BASED SOLUTIONS ON FLOOD VULNERABILITY AND LOSS IN SMALL URBANIZING REGIONS: A CASE STUDY OF THE PHILADELPHIA METROPOLITAN AREA
… using the Generalized Linear Model (GLR) and Geographically Weighted Regression (GWR) techniques was examined. The findings partially contradicted previous research by revealing an unexpected relationship between NbS quantity in floodplains and expected annual loss. Findings also demonstrated …
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Spatio-temporal modeling of Louisiana land subsidence using high resolution geo-spatial data
… we have used some geo-statistics models, such as Geographically Weighted Regression (GWR), the spatial-lag model and the spatial-error model, so as to find which main factors have caused adverse subsidence in the study site in 2013 (Mardia et al. 1998; Fotheringham et al. 2002; Baller et al. 2001; …
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Modularized Bayesian Inference: Methodology, Algorithm, Theory And Application.
… Interestingly, this feature corresponds to a geographically weighted regression (GWR) model that has been developed to handle the spatial non-stationarity but hitherto not been extended to Bayesian inference except for the Gaussian regression. This thesis proposes the Bayesian GWR model as a …
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Revisiting the Housing Allowance Algorithm and its Theoretical Implications on Rental Housing Demand and Rents. Evidence from New Zealand.
… Area Units that are not time invariant via a Geographically Weighted Regression (GWR) to complement the analysis. Contrary to what is argued in the literature, I find statistically significant results for the increase in the subsidy’s demand and cost at the submarket level to affect market …
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Maternal and child health outcomes in relation to accessibility, spatial distribution, inequality and free maternal care in Kenya
… the 2003 and 2014 surveys. Secondly, a logit regression model is used to examine the factors that determine the utilization of maternal health care when supply-side factors are controlled for. As expected, utilization of maternal health care is found to increase with increases in maternal …
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Analysis of Gentrification and Green Spaces in East Austin, Texas
… 2010-2015 and 2017-2022 through use of spatial regression and buffer zone techniques. These tools revealed the parks that are experiencing green gentrification in the study area. In order to determine if the ‘Imagine Austin’ plan had an impact on the gentrification in the targeted area, the …
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Spatial urban environmental change and Malaria/Diarrhoea mortality in Accra, Ghana
… Morans I and other geo-statistical approaches (geographically weighted regression GWR and LISA) to assess the spatial associations between the health summary measure on the one hand and the socioeconomic and environmental conditions on the other hand. Results: For demographic and health …