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Xiang Ye

Dados Biográficos

ID9501971
NOMEXiang Ye
PRENOMESXiang
SOBRENOMEYe
ASSINATURAYE X
AFILIAÇÕESResearch Institute for Smart Cities Shenzhen University Shenzhen Guangdong 518060 P. R. China
ORCID0000-0002-2283-2591
VERIFICADOSim
TOTAL DE OBRAS5
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR5
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2022
ANO MAIS RECENTE DE PUBLICAÇÃO2025
ÍNDICE H0
  • Modelling super-diffusion in urban human mobility

    Open Access•Luojian Tan, Linwang Yuan et al.•ARTICLE•Cities•2025

  • Flow Spatiotemporal Moran's I

    Open Access•Qingyang Fu, Mengjie Zhou et al.•ARTICLE•Geographical Analysis•2024

    Flows can reflect the spatiotemporal interactions or movements of geographical objects between different locations. Measuring the spatiotemporal autocorrelation of flows can help determine the overall spatiotemporal trends and local patterns. However, quantitative indicators of flows used to measure spatiotemporal autocorrelation both globally and locally are still rare. Therefore, we propose the global and local flow spatiotemporal Moran's I (FS…

  • Effects of Linpan nature therapy on health benefits in older women with and without hypertension

    Open Access•Ye Xiang, Xiang Ye et al.•ARTICLE•Frontiers in Public Health•2023

    Background: Nature therapy can significantly benefit the physiology and psychology of middle-aged and older people, but previous studies have focused on forest environments. The restoration potential of rural environments in urban fringe areas, which are more accessible to older people on a daily basis, has not been fully studied. This study assessed the effects of nature therapy on the physical and mental health of older women in a rural setting…

  • Estimating σ 2 for the Classical Linear Regression Model (CLRM) with the Presence of the Modifiable Areal Unit Problem (Maup)

    Open Access•Xiang Ye•ARTICLE•Geographical Analysis•2022

    In a classical linear regression model (CLRM), the magnitude of disturbances is characterized by σ 2 . When individual observations are aggregated into regions, the modifiable areal unit problem (MAUP) appears. The presence of the MAUP brings significant challenges to estimating σ 2 , as the traditional ordinary least square estimator at the individual level, s 2 , becomes downward biased at the aggregate level. Based on the information available…

  • The Impacts of the Modifiable Areal Unit Problem (Maup) on Omission Error

    Open Access•Xiang Ye, Peter A Rogerson•ARTICLE•Geographical Analysis•2022

    An omission error occurs when independent variables are missing from a regression model. When individual observations are not available, the modifiable areal unit problem (MAUP) appears with spatially aggregated data sets. Both omission error and the MAUP can occur simultaneously in regression analyses. In particular, the MAUP causes the bias due to an omission error to be less predictable for linear regression models, and it distorts bias differ…

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  • Estimating σ 2 for the Classical Linear Regression Model (CLRM) with the Presence of the Modifiable Areal Unit Problem (Maup)

    Open Access•Xiang Ye•ARTICLE•Geographical Analysis•2022

    In a classical linear regression model (CLRM), the magnitude of disturbances is characterized by σ 2 . When individual observations are aggregated into regions, the modifiable areal unit problem (MAUP) appears. The presence of the MAUP brings significant challenges to estimating σ 2 , as the traditional ordinary least square estimator at the individual level, s 2 , becomes downward biased at the aggregate level. Based on the information available…

  • The Impacts of the Modifiable Areal Unit Problem (Maup) on Omission Error

    Open Access•Xiang Ye, Peter A Rogerson•ARTICLE•Geographical Analysis•2022

    An omission error occurs when independent variables are missing from a regression model. When individual observations are not available, the modifiable areal unit problem (MAUP) appears with spatially aggregated data sets. Both omission error and the MAUP can occur simultaneously in regression analyses. In particular, the MAUP causes the bias due to an omission error to be less predictable for linear regression models, and it distorts bias differ…

  • Effects of Linpan nature therapy on health benefits in older women with and without hypertension

    Open Access•Ye Xiang, Xiang Ye et al.•ARTICLE•Frontiers in Public Health•2023

    Background: Nature therapy can significantly benefit the physiology and psychology of middle-aged and older people, but previous studies have focused on forest environments. The restoration potential of rural environments in urban fringe areas, which are more accessible to older people on a daily basis, has not been fully studied. This study assessed the effects of nature therapy on the physical and mental health of older women in a rural setting…

  • Flow Spatiotemporal Moran's I

    Open Access•Qingyang Fu, Mengjie Zhou et al.•ARTICLE•Geographical Analysis•2024

    Flows can reflect the spatiotemporal interactions or movements of geographical objects between different locations. Measuring the spatiotemporal autocorrelation of flows can help determine the overall spatiotemporal trends and local patterns. However, quantitative indicators of flows used to measure spatiotemporal autocorrelation both globally and locally are still rare. Therefore, we propose the global and local flow spatiotemporal Moran's I (FS…

  • Modelling super-diffusion in urban human mobility

    Open Access•Luojian Tan, Linwang Yuan et al.•ARTICLE•Cities•2025

Mathematics (4 obras) · Statistics (4 obras) · Econometrics (3 obras) · Economic and Environmental Valuation (3 obras) · Aggregate (composite) (2 obras) · Housing Market and Economics (2 obras) · Linear regression (2 obras) · Physics (2 obras) · Spatial and Panel Data Analysis (2 obras) · Statistical physics (2 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae