How do varying socio-economic driving forces affect China’s carbon emissions? New evidence from a multiscale geographically weighted regression model
Sign Up to like & getrecommendations! Published in 2021 at "Environmental Science and Pollution Research"
DOI: 10.1007/s11356-021-13444-1
Abstract: The increase in carbon emissions has had great negative impacts on the healthy developments of the human environment and economic society. However, it is unclear how specific socio-economic factors are driving carbon emissions. Based on… read more here.
Keywords: carbon emissions; weighted regression; carbon; china carbon ... See more keywords
A geographically and temporally weighted regression model for assessing intra-urban variability of volatile organic compounds (VOCs) in Yangpu district, Shanghai
Sign Up to like & getrecommendations! Published in 2019 at "Atmospheric Environment"
DOI: 10.1016/j.atmosenv.2019.06.052
Abstract: Abstract The adverse health effects of volatile organic compounds (VOCs) highlight the need of spatiotemporal models to assess exposure for epidemiological studies. Herein, a geographically and temporally weighted regression (GTWR) model was developed to estimate… read more here.
Keywords: volatile organic; temporally weighted; model; district ... See more keywords
Mapping topsoil electrical conductivity by a mixed geographically weighted regression kriging: A case study in the Heihe River Basin, northwest China
Sign Up to like & getrecommendations! Published in 2019 at "Ecological Indicators"
DOI: 10.1016/j.ecolind.2019.02.038
Abstract: Abstract Spatial prediction is an important approach to obtain location-specific values of soil electrical conductivity (EC), which is a proxy of soil salinity and important for agricultural management in arid and semi-arid areas. Linear regression… read more here.
Keywords: regression; mixed geographically; geographically weighted; river basin ... See more keywords
Scale-adaptive estimation of mixed geographically weighted regression models
Sign Up to like & getrecommendations! Published in 2021 at "Economic Modelling"
DOI: 10.1016/j.econmod.2020.02.015
Abstract: Abstract Mixed geographically weighted regression (GWR) models, a combination of linear and spatially varying coefficient models, have found their applications in a variety of disciplines including economic modelling for geo-referenced data analysis. Generally, different explanatory… read more here.
Keywords: weighted regression; estimation; scale adaptive; mixed geographically ... See more keywords
Geographical analysis of CO2 emissions in China's manufacturing industry: A geographically weighted regression model
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Cleaner Production"
DOI: 10.1016/j.jclepro.2017.08.052
Abstract: Abstract At present, China's carbon dioxide (CO 2 ) emissions ranked first in the world. Moreover, the CO 2 emissions in the manufacturing industry accounted for 55.0% of total CO 2 emissions. Thus, investigating the… read more here.
Keywords: weighted regression; manufacturing industry; regression; geographically weighted ... See more keywords
Robust weighted regression via PAELLA sample weights
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.03.108
Abstract: Abstract This paper reports the usage of the occurrence vector provided by the PAELLA algorithm in the context of robust regression. PAELLA was originally conceived as an outlier detection and data cleaning technique. A novel… read more here.
Keywords: weighted regression; paella; regression; via paella ... See more keywords
Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model
Sign Up to like & getrecommendations! Published in 2017 at "Remote Sensing of Environment"
DOI: 10.1016/j.rse.2017.06.001
Abstract: Abstract Most time-sequenced ambient air pollution data in China is published through daily Air Quality Index (AQI). However, few studies have used the AQI data to calibrate satellite-based estimates of fine particulate matter (PM 2.5… read more here.
Keywords: weighted regression; regression; gtwr model; model ... See more keywords
Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting
Sign Up to like & getrecommendations! Published in 2018 at "Transportation Planning and Technology"
DOI: 10.1080/03081060.2018.1526988
Abstract: ABSTRACT In recent years, there has been considerable research interest in short-term traffic flow forecasting. However, forecasting models offering a high accuracy at a fine temporal resolution (e.g. 1 or 5 min) and lane level are… read more here.
Keywords: traffic; weighted regression; traffic flow; locally weighted ... See more keywords
Prediction of soil salinity in the Yellow River Delta using geographically weighted regression
Sign Up to like & getrecommendations! Published in 2017 at "Archives of Agronomy and Soil Science"
DOI: 10.1080/03650340.2016.1249475
Abstract: ABSTRACT It is essential to determine the content and spatial distribution of soil salinity in a timely manner because soil salinization can cause land degradation on a regional scale. Geographically weighted regression (GWR) is a… read more here.
Keywords: soil; weighted regression; soil salinity; geographically weighted ... See more keywords
On the notion of ‘bandwidth’ in geographically weighted regression models of spatially varying processes
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2022.2034829
Abstract: Abstract Models designed to capture spatially varying processes are now employed extensively in the social and environmental sciences. The main strength of such models is their ability to represent relationships that vary across locations through… read more here.
Keywords: notion bandwidth; geographically weighted; weighted regression; varying processes ... See more keywords
Geographically Weighted Regression Analysis for Spatial Economics Data: A Bayesian Recourse
Sign Up to like & getrecommendations! Published in 2020 at "International Regional Science Review"
DOI: 10.1177/0160017620959823
Abstract: The geographically weighted regression (GWR) is a well-known statistical approach to explore spatial non-stationarity of the regression relationship in spatial data analysis. In this paper, we discuss a Bayesian recourse of GWR. Bayesian variable selection… read more here.
Keywords: weighted regression; methodology; analysis; geographically weighted ... See more keywords