Evaluating Geographically Weighted Regression Models for Environmental Chemical Risk Analysis [PDF]
Cancer Informatics, 2015 In the evaluation of cancer risk related to environmental chemical exposures, the effect of many correlated chemicals on disease is often of interest. The relationship between correlated environmental chemicals and health effects is not always constant ...
Jenna Czarnota +2 more
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A modification to geographically weighted regression
International Journal of Health Geographics, 2017 Background Geographically weighted regression (GWR) is a modelling technique designed to deal with spatial non-stationarity, e.g., the mean values vary by locations. It has been widely used as a visualization tool to explore the patterns of spatial data.
Yin-Yee Leong, Jack C. Yue
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Improving Victimization Risk Estimation: A Geographically Weighted Regression Approach
ISPRS International Journal of Geo-Information, 2021 Standardized crime rates (e.g., “homicides per 100,000 people”) are commonly used in crime analysis as indicators of victimization risk but are prone to several issues that can lead to bias and error.
Rafael G. Ramos
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Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data [PDF]
Acta Amazonica, 2016 The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome.
Fátima L. BENÍTEZ +2 more
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PEMILIHAN VARIABEL PADA MODEL GEOGRAPHICALLY WEIGHTED REGRESSION
Media Statistika, 2011 Regression analysis is a statistical analysis that aims to model the relationship between response variable with some predictor variables. Geographically Weighted Regression (GWR) is statistical method used for analyzed the spatial data in local form of ...
Hasbi Yasin
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Geographically Weighted Probit Ordinal Regression Model Estimation [PDF]
E3S Web of ConferencesGeographically Weighted Probit Ordinal Regression (GWPOR) is a combined method between Geographically Weighted Regression and Probit Ordinal Regression. This study estimates the percentage of poor people using the GWPOR method.
Kurniawan Muh. Idham +2 more
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Analyzing Determinants of Spatial Patterns in Total and Industrial Electricity Consumption in Turkey [PDF]
Statistika: Statistics and Economy JournalThis research investigates the spatial correlation among per capita electricity consumption, per capita industrial electricity consumption, and economic growth by employing various regression models, including linear regression, geographically weighted ...
Semra Türkan
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Spatial prediction of flood-prone areas using geographically weighted regression
Environmental Advances, 2021 An important non-structural solution in flood management is susceptibility mapping, which identifies the likelihood of flood occurrence in an area.
Jia Min Lin, Lawal Billa
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Geographically weighted elastic net logistic regression [PDF]
, 2018 This paper develops a localized approach to elastic net logistic regression, extending previous research describing a localized elastic net as an extension to a localized ridge regression or a localized lasso.
Comber, A. +3 more
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Satellite and gauge rainfall merging using geographically weighted regression [PDF]
Proceedings of the International Association of Hydrological Sciences, 2015 A residual-based rainfall merging scheme using geographically weighted regression (GWR) has been proposed. This method is capable of simultaneously blending various satellite rainfall data with gauge measurements and could describe the non-stationary ...
Q. Hu +4 more
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