Modeling Anisotropy and Non‐Stationarity Through Physics‐Informed Spatial Regression
Sign Up to like & getrecommendations! Published in 2024 at "Environmetrics"
DOI: 10.1002/env.2889
Abstract: Many spatially dependent phenomena that are of interest in environmental problems are characterized by strong anisotropy and non‐stationarity. Moreover, the data are often observed over regions with complex conformations, such as water bodies with complicated… read more here.
Keywords: anisotropy non; anisotropy; non stationarity; physics ... See more keywords
Comparison between spatial and non-spatial regression models for investigating tree–soil relationships in a polycyclic tree plantation of Northern Italy and implications for management
Sign Up to like & getrecommendations! Published in 2018 at "Agroforestry Systems"
DOI: 10.1007/s10457-018-0334-3
Abstract: Although there is greater awareness of spatial variability of factors affecting plant growth, regression methods with residuals independently and identically distributed, are still used. Thus, we compared spatial and non-spatial regression models in evaluating the… read more here.
Keywords: spatial regression; non spatial; soil; growth ... See more keywords
Birnbaum-Saunders spatial regression models: Diagnostics and application to chemical data
Sign Up to like & getrecommendations! Published in 2018 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2018.03.012
Abstract: Abstract Geostatistical modelling is widely used to describe data with spatial dependence structure. Such modelling often assumes a Gaussian distribution, an assumption which is frequently violated due to the asymmetric nature of variables in diverse… read more here.
Keywords: spatial regression; chemical data; saunders spatial; birnbaum saunders ... See more keywords
A spatial regression and clustering method for developing place-specific social vulnerability indices using census and social media data
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Disaster Risk Reduction"
DOI: 10.1016/j.ijdrr.2019.101224
Abstract: Abstract This paper presents a new social vulnerability index construction approach that utilizes geographically weighted local regression modeling and spatial clustering to determine location-specific weights of vulnerability indicators. Sub-regions within the study region with homogeneous… read more here.
Keywords: regression; spatial regression; social media; vulnerability ... See more keywords
Measurement Error and the Specification of the Weights Matrix in Spatial Regression Models
Sign Up to like & getrecommendations! Published in 2019 at "Political Analysis"
DOI: 10.1017/pan.2019.35
Abstract: While the spatial weights matrix $\boldsymbol{W}$ is at the core of spatial regression models, there is a scarcity of techniques for validating a given specification of $\boldsymbol{W}$. I approach this problem from a measurement error… read more here.
Keywords: spatial regression; regression; weights matrix; regression models ... See more keywords
Risk exposure factors influencing the frequency of road crashes during the COVID-19 pandemic in Ciudad Juarez, Mexico. A negative binomial spatial regression model.
Sign Up to like & getrecommendations! Published in 2023 at "International journal of injury control and safety promotion"
DOI: 10.1080/17457300.2023.2188469
Abstract: The article aims to investigate the influence of risk exposure factors on the frequency of road crashes from January to August 2020 in Ciudad Juarez, Mexico. It is a longitudinal study with four data sets:… read more here.
Keywords: road; road crashes; frequency road; spatial regression ... See more keywords
Two-stage estimators for spatial confounding with point-referenced data
Sign Up to like & getrecommendations! Published in 2024 at "Biometrics"
DOI: 10.1093/biomtc/ujaf093
Abstract: ABSTRACT Public health data are often spatially dependent, but standard spatial regression methods can suffer from bias and invalid inference when the independent variable is associated with spatially correlated residuals. This could occur if, for… read more here.
Keywords: estimators spatial; point referenced; referenced data; regression ... See more keywords
Using Web-Data to Estimate Spatial Regression Models
Sign Up to like & getrecommendations! Published in 2023 at "International Regional Science Review"
DOI: 10.1177/01600176231173438
Abstract: Macro econometrics has been recently affected by the so-called ‘Google Econometrics’. Comparatively less attention has been paid to the subject by the regional and spatial sciences where the Big Data revolution is challenging the conventional… read more here.
Keywords: estimate spatial; regression; data estimate; web data ... See more keywords
BARcode DEmixing through Non-negative Spatial Regression (BarDensr)
Sign Up to like & getrecommendations! Published in 2021 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1008256
Abstract: Modern spatial transcriptomics methods can target thousands of different types of RNA transcripts in a single slice of tissue. Many biological applications demand a high spatial density of transcripts relative to the imaging resolution, leading… read more here.
Keywords: demixing non; spatial regression; barcode demixing; regression bardensr ... See more keywords
Driving Factors of NOx Emissions in China: Insights from Spatial Regression Analysis
Sign Up to like & getrecommendations! Published in 2024 at "Atmosphere"
DOI: 10.3390/atmos15070793
Abstract: China’s rapid industrialization and urbanization have led to significant nitrogen oxide (NOx) emissions, contributing to severe atmospheric pollution. Understanding the driving factors behind these emissions is crucial for effective pollution control and environmental management. Therefore,… read more here.
Keywords: nox emissions; driving factors; emissions china; factors nox ... See more keywords
Detection of Influential Observations in Spatial Regression Model Based on Outliers and Bad Leverage Classification
Sign Up to like & getrecommendations! Published in 2021 at "Symmetry"
DOI: 10.3390/sym13112030
Abstract: Influential observations (IOs), which are outliers in the x direction, y direction or both, remain a problem in the classical regression model fitting. Spatial regression models have a peculiar kind of outliers because they are… read more here.
Keywords: spatial regression; influential observations; bad leverage; regression model ... See more keywords