Geographically Weighted Regression (GWR)
Modelação das taxas de mortalidade associadas a hábitos alimentares nos municípios portugueses -uma análise exploratória utilizando geographically weighted regression
... linear regression models, choosing the best possible model according to multiple statistical tests and diagnostic ...a Geographically Weighted Regression (GWR) model with the variables that ...
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Modeling malaria cases associated with environmental risk factors in Ethiopia using geographically weighted regression
... (OLS), geographically weighted regression (GWR), and semiparametric geographically weighted regression (s-GWR) models were compared to describe the spatial association of ...
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MAPPING OF ILLITERACY AND INFORMATION AND COMMUNICATION TECHNOLOGY INDICATORS USING GEOGRAPHICALLY WEIGHTED REGRESSION
... Geographically Weighted Regression (GWR) is a technique that brings the framework of a simple regression model into a weighted regression ...bandwidth, weighted by kernel ...
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AN INVESTIGATION OF LOCAL EFFECTS ON SURFACE WARMING WITH GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)
... utilizing Geographically Weighted Regression (GWR) to analyze the spatial relationship between urban form and surface temperature variation in order to clarify the local effects on surface warming, ...
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Testing the water-energy theory on American palms (Arecaceae) using geographically weighted regression.
... Geographically weighted regression (GWR) is a geographically local modeling technique specifically designed to deal with spatial non-stationarity in the modeled relationships ...one ...
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Modelling youth pregnancy in continental Portugal through geographically weighted regression
... Youth pregnancy, a global public health problem with impor- tant social, educational and economic impact, has mostly been studied in the least developed countries. However, this condition also affects the industrialized ...
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A geographically weighted regression approach to investigate air pollution effect on lung cancer
... a regression point that is weighted by the distance of the point ...classical regression models (Foody, 2003). GWR extends the global regression technique by allowing local parameters to be ...
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A geographically weighted regression approach to investigate air pollution effect on lung cancer : a case study
... Poisson regression, where the observed cases are the dependent variable, the expected cases compensated and two types of terms of random effects that take into account both spatial continuity and spatial ...
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Análise espacial dos resultados eleitorais em Portugal – Aplicação do Geographically Weighted Regression
... A partir do ficheiro de resultados do “ output” do modelo de regressão dos resultados do Partido Comunista Português podemos concluir, por comparação que existe uma sig[r] ...
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Weighted Marking, Clique Structure and Node-Weighted Centrality to Predict Distribution Centre’s Location in a Supply Chain Management
... of weighted networks, they carried out statistical analysis of complex networks whose edges have assigned a given weight (the flow or the intensity), and such according to them can generally be described in terms ...
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Revisit of Logistic Regression
... In the experimental results on multi-class classifications using various datasets, the proposed methods exhibit favorable performances in terms of classification accuracies and computati[r] ...
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A Matlab program for stepwise regression
... linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation (Zhang and Fang, ...
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ON INTERVAL ESTIMATING REGRESSION
... The main motivation of the research presented in this paper is the 50 th anniversary of very simple nonparametric regression function estimator – the Nadaraya-Watson kernel estimator. It was invented independently ...
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A Tutorial on Logistic Regression
... This is consistent with the cumulative logit model, though this may not always be desirable because 1 is often used to denote the response of the event of interest. Consider the following logistic regression ...
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Alternative Fuzzy Switching Regression
... switching regression can not be written as a matrix form such as the traditional regression ...switching regression models ...traditional weighted least square ...
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Weighted Twin Support Vector Machine with Universum
... From the above description, we know that �-TSVM uses hinge loss function just as �-SVM, so this algorithm is less robust, in other words, sensitive to noises. This is the common drawback of any learning method using ...
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Penalized regression methods for compositional data
... 2015 ). However, a remarkable disadvantage about the clr transformation is that the variance matrix of its transformed composition is unique. Furthermore, the alr coordinates are non- isometric and asymmetric and the clr ...
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Revenue management through regression analysis
... linear regression approach is used to model the relationship between the dependent variable (demand) and the independent variables ...time…). Regression analysis is a commonly used method for obtaining a ...
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Weighted hardy operators in complementary morrey spaces
... The paper is organized as follows. In Section 2 we give definitions and necessary preliminaries, including conditions for radial functions to belong to complementary Morrey spaces. In Section 3 we prove the ...
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Weighted Scale-Free Random Graph Model
... Abstract—Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free ...
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