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Showing 1 to 20 of 31 for “"GWR"”.

  1. Spatial Data Analysis

    Devkota, Mitra Lal2017

    … (LME), and Geographically Weighted Regression (GWR) were discussed. Comparative studies of these modeling techniques were carried out using a real world dataset and an artificially generated spatial dataset. In chapter 3, a recently developed spatial analytical tool, Geographically Weighted …

    sdstate Repository record

  2. Factors influencing hunting license sales in urban and rural areas of Illinois

    Zhang, XiaohanUniversity of Illinois at Urbana-Champaign2020

    … local model (geographically weighted regression [GWR]) were applied to deal with spatial autocorrelation of the residuals. The first part found that accessibility to hunting resources, economic status, age structure, education, race and ethnicity, and competition with general recreation influenced …

    uiuc Repository record

  3. Spatio-temporal modeling of Louisiana land subsidence using high resolution geo-spatial data

    Xiang, HanyuGeography and Anthropology2022

    … 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; Wang 2006; Wang et al. 2014; …

    lsu-thes Repository record

  4. Modularized Bayesian Inference: Methodology, Algorithm, Theory And Application.

    Liu, YangUniversity of Cambridge2022

    … 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 certain multiple-module case of …

    cambridge Repository record

  5. The Spatial Relationships among Neurotoxicant Exposure, Child Admissions, and Mental Health Assessment Scores: How do they Interact in the State of Ohio?

    Massatti, Richard RolandThe Ohio State University2013

    … models and geographic weighted regression (GWR) was used to examine local relationships.GWR models explained a large percentage of the variance in child admissions (46%) and attention deficit-hyperactivity disorder (AD-HD) admissions (40%); however, the total hazard quotient for …

    ohiolink Repository record

  6. GIS-based urban land use characterization and population modeling with subpixel information measured from remote sensing data

    Tang, QuanGeography and Anthropology2022

    … the population distribution. Both the OLS and GWR models produced poor model fit. In contrast, the land use information extracted from the V-I-S information and LST significantly improved regression models. A three-class land use model is fitted adequately. The GWR model reveals the spatial …

    lsu-thes Repository record

  7. 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

    Erdem, MustafaGeography and Anthropology2018

    … 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 study have generated empirically-based and useful …

    lsu-thes Repository record

  8. Spatial and Spatiotemporal Modeling of Epidemiological Data

    Karki, Laxman2017

    … Various types of regression methods such as OLS, GWR and MGWR were used to study the association between diabetes prevalence and socioeconomic and lifestyle factors on county level data of Midwestern United States. A new analysis workflow is purposed for regression analysis of spatial data. …

    sdstate Repository record

  9. Artificial Intelligence and Spatial Modeling to Estimate Traffic Volume Measures on Local Roadways

    Mimi, Mahmuda SultanaTexas State University2025

    … 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 the importance of spatial …

    texas-state Repository record

  10. Choosing success? Inequalities and opportunities in access to school choice in nine United States districts

    Rangel, ClaudiaUniversity of Illinois at Urbana-Champaign2013

    … 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 variation of school choice accessibility, …

    uiuc Repository record

  11. Spatial Patterns and Variations of Tornado Damage as Related to Southeastern Appalachian Forests and Terrain from the Franklin County, Virginia EF-3 Tornado

    Forister, Peter HardingVirginia Tech2021

    … OLS and geographically weighted regression (GWR) modeling performed poorly, suggesting that an alternative method may be more suitable for modeling, the scale of assessment was inadequate, or that important predictor variables were not captured. Overall, the intensity of the tornado was …

    vt Repository record

  12. Optimum Timing for CO2-EOR After Waterflooding and Soaking Effect on Miscible CO2 Flooding in a Tight Sandstone Formation,

    Li, ZeyaFaculty of Graduate Studies and Research, University of Regina2014

    … CO2- saturated light oil, and gas–water ratio (GWR) of CO2-saturated reservoir brine were measured by using a PVT system. Second, the viscosities of CO2-saturated light oil with different CO2 concentrations were measured by using a capillary viscometer. Third, the equilibrium interfacial …

    regina Repository record

  13. Forecasting the use of new local railway stations and services using GIS

    Blainey, Simon PhilipUniversity of Southampton2009

    … 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 stations in South-East Wales, with a range …

    soton Repository record

  14. From Section 8 to Starbucks: The Effects of Gentrification on Affordable Housing in Pittsburgh, Pennsylvania

    Kozak, Stephanie L.University of Kansas2014

    … 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 reducing the availability of affordable housing in the Pittsburgh metro, despite the presence of …

    ku Repository record

  15. Integrating AI and GIS for Climate-Driven Malaria Monitoring and Demand-Based Resource Distribution and Supply Optimization in Low Developing Countries

    Komugabe, Maria Assumpta2026

    … (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 reliable 30-day (Lag-1) lead …

    claremont Repository record

  16. Understanding Colombian Violence Through Geographic Information Systems and Statistical Approaches

    Fowler, Brandon

    … rates. Regression models, specifically OLS and GWR, were utilized to examine the relationships between homicide rates and an assortment of geographic factors, including Coca Cultivation Density<em>, <em>Presidential Election Participation Rate</em>, <em>Displaced Persons </em></em>Rate<em>, …

    wku-diss Repository record

  17. Geographic Factors of Residential Burglaries - A Case Study in Nashville, Tennessee

    Hall, Jonathan A.

    … factors of residential burglary, both OLS and GWR regression analyses are conducted to examine the relationships between residential burglary rates and various geographic factors, such as Percentages of Minorities, Singles, Vacant Housing Units, Renter Occupied Housing Units, and Persons below …

    wku-diss Repository record

  18. Vegetation growing season length along the urban-rural gradients across European capital cities

    Ojasalo, AmandaHelsingin yliopisto2024

    … maantieteellisesti painotetun regressiomallin (GWR) avulla, joka ottaa huomioon eri muuttujien vaikutusten spatiaaliset eroavaisuudet. Lopulliset muuttujat mallissa olivat pintalämpötila, urbaani maanpeite yli 30 % peitetyllä maalla, sekä lehtipuiden osuus. Näiden kolmen muuttujan vaikutus oli …

    helsinki Repository record

  19. Landscape patterns and patch dynamics in Hamilton county over a forty year period: applicability to the conservation of the eastern box turtle

    Colson, Marie2009

    … (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. Regression model residual analysis …

    utc Repository record

  20. The Use of Remote Sensing for Mapping Possible Vectors of West Nile Virus in Mississippi

    Moore, Brian Matthew2018

    … and geographic weighted regression (GWR), were used to predict mosquito abundance and to map possible West Nile virus vector distribution and abundance. A raster data model with 30m x 30m cell size was used to explore research questions. Results indicate NDVI, soil, and DEM are the …

    usm Repository record

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