Lianfa Li
Datos Biográficos
| ID | 3584403 |
|---|---|
| NOMBRE | Lianfa Li |
| NOMBRES | Lianfa |
| APELLIDO | Li |
| FIRMA | LI L |
| AFILIACIONES | Chinese Academy of Sciences |
| ORCID | 0000-0002-9382-8637 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 8 |
| TOTAL DE CITAS | 17 |
| TOTAL COMO AUTOR | 8 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2012 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2024 |
| ÍNDICE H | 3 |
Statistical Modeling of Spatially Stratified Heterogeneous Data
Spatial statistics is an important methodology for geospatial data analysis. It has evolved to handle spatially autocorrelated data and spatially (locally) heterogeneous data, which aim to capture the first and second laws of geography, respectively. Examples of spatially stratified heterogeneity (SSH) include climatic zones and land-use types. Methods for such data are relatively underdeveloped compared to the first two properties. The presence …
Dynamic relationship between the stock market and macroeconomy in China (1995–2018)
This article examines the relationship between the stock market and three widely used macroeconomic variables, namely industrial production growth, inflation, and long-term interest rate in China. We use the continuous wavelet analysis to investigate the correlations and lead–lag relationships between them in the time–frequency domain by covering a period of 1995M01-2018M04. Our findings show the positive relationship between stock returns and in…
A spatiotemporal mixed model to assess the influence of environmental and socioeconomic factors on the incidence of hand, foot and mouth disease
We developed a geo-additive mixed spatiotemporal model to assess the influence of meteorological, environmental and socioeconomic factors on HFMD incidence and explored spatiotemporal patterns of such incidence. Our approach achieved a competitive performance in cross-validation and revealed strong spatial patterns for the HFMD incidence rate, illustrating important implications for the epidemiology of HFMD
An Ensemble Spatiotemporal Model for Predicting PM2.5 Concentrations
Although fine particulate matter with a diameter of 2.5 ) has a greater negative impact on human health than particulate matter with a diameter of 10 ), measurements of PM 2.5 have only recently been performed, and the spatial coverage of these measurements is limited. Comprehensively assessing PM 2.5 pollution levels and the cumulative health effects is difficult because PM 2.5 monitoring data for prior time periods and certain regions are not a…
Cardiovascular Mortality Associated with Low and High Temperatures
The objectives of this study were to estimate the effects of temperature on cardiovascular mortality in 26 regions in the south and west of China from 2008 to 2011, and to identify socioeconomic and demographic factors contributing to such inter-region variation in the temperature effect. A separate Poisson generalized additive model (GAM) was fitted to estimate percent changes in cardiovascular mortality at low and high temperatures on a daily b…
Green spaces and pregnancy outcomes in Southern California
Sandwich Estimation for Multi-Unit Reporting on a Stratified Heterogeneous Surface
Spatial sampling is widely used in environmental and social research. In this paper we consider the situation where instead of a single global estimate of the mean of an attribute for an area, estimates are required for each of many geographically defined reporting units (such as counties or grid cells) because their means cannot be assumed to be the same as the global figure. Not only may survey costs greatly increase if sample size has to be a …
A spatial model to predict the incidence of neural tube defects
Environmental exposure may play an important role in the incidences of neural tube defects (NTD) of birth defects. Their influence on NTD may likely be non-linear; few studies have considered spatial autocorrelation of residuals in the estimation of NTD risk. We aimed to develop a spatial model based on generalized additive model (GAM) plus cokriging to examine and model the expected incidences of NTD and make the inference of the incidence risk.…
Statistical Modeling of Spatially Stratified Heterogeneous Data
Spatial statistics is an important methodology for geospatial data analysis. It has evolved to handle spatially autocorrelated data and spatially (locally) heterogeneous data, which aim to capture the first and second laws of geography, respectively. Examples of spatially stratified heterogeneity (SSH) include climatic zones and land-use types. Methods for such data are relatively underdeveloped compared to the first two properties. The presence …
Green spaces and pregnancy outcomes in Southern California
Sandwich Estimation for Multi-Unit Reporting on a Stratified Heterogeneous Surface
Spatial sampling is widely used in environmental and social research. In this paper we consider the situation where instead of a single global estimate of the mean of an attribute for an area, estimates are required for each of many geographically defined reporting units (such as counties or grid cells) because their means cannot be assumed to be the same as the global figure. Not only may survey costs greatly increase if sample size has to be a …
A spatial model to predict the incidence of neural tube defects
Environmental exposure may play an important role in the incidences of neural tube defects (NTD) of birth defects. Their influence on NTD may likely be non-linear; few studies have considered spatial autocorrelation of residuals in the estimation of NTD risk. We aimed to develop a spatial model based on generalized additive model (GAM) plus cokriging to examine and model the expected incidences of NTD and make the inference of the incidence risk.…
Green spaces and pregnancy outcomes in Southern California
Sandwich Estimation for Multi-Unit Reporting on a Stratified Heterogeneous Surface
Spatial sampling is widely used in environmental and social research. In this paper we consider the situation where instead of a single global estimate of the mean of an attribute for an area, estimates are required for each of many geographically defined reporting units (such as counties or grid cells) because their means cannot be assumed to be the same as the global figure. Not only may survey costs greatly increase if sample size has to be a …
Cardiovascular Mortality Associated with Low and High Temperatures
The objectives of this study were to estimate the effects of temperature on cardiovascular mortality in 26 regions in the south and west of China from 2008 to 2011, and to identify socioeconomic and demographic factors contributing to such inter-region variation in the temperature effect. A separate Poisson generalized additive model (GAM) was fitted to estimate percent changes in cardiovascular mortality at low and high temperatures on a daily b…
An Ensemble Spatiotemporal Model for Predicting PM2.5 Concentrations
Although fine particulate matter with a diameter of 2.5 ) has a greater negative impact on human health than particulate matter with a diameter of 10 ), measurements of PM 2.5 have only recently been performed, and the spatial coverage of these measurements is limited. Comprehensively assessing PM 2.5 pollution levels and the cumulative health effects is difficult because PM 2.5 monitoring data for prior time periods and certain regions are not a…
A spatiotemporal mixed model to assess the influence of environmental and socioeconomic factors on the incidence of hand, foot and mouth disease
We developed a geo-additive mixed spatiotemporal model to assess the influence of meteorological, environmental and socioeconomic factors on HFMD incidence and explored spatiotemporal patterns of such incidence. Our approach achieved a competitive performance in cross-validation and revealed strong spatial patterns for the HFMD incidence rate, illustrating important implications for the epidemiology of HFMD
Dynamic relationship between the stock market and macroeconomy in China (1995–2018)
This article examines the relationship between the stock market and three widely used macroeconomic variables, namely industrial production growth, inflation, and long-term interest rate in China. We use the continuous wavelet analysis to investigate the correlations and lead–lag relationships between them in the time–frequency domain by covering a period of 1995M01-2018M04. Our findings show the positive relationship between stock returns and in…
Statistical Modeling of Spatially Stratified Heterogeneous Data
Spatial statistics is an important methodology for geospatial data analysis. It has evolved to handle spatially autocorrelated data and spatially (locally) heterogeneous data, which aim to capture the first and second laws of geography, respectively. Examples of spatially stratified heterogeneity (SSH) include climatic zones and land-use types. Methods for such data are relatively underdeveloped compared to the first two properties. The presence …
Mathematics (7 obras) · Statistics (7 obras) · Econometrics (4 obras) · Geography (4 obras) · Medicine (4 obras) · Air Quality and Health Impacts (3 obras) · Generalized additive model (3 obras) · Population (3 obras) · Spatial analysis (3 obras) · Spatial and Panel Data Analysis (3 obras)