scholarly journals Balancing Spatial and Non‐Spatial Variation in Varying Coefficient Modeling: A Remedy for Spurious Correlation

2021 ◽  
Author(s):  
Daisuke Murakami ◽  
Daniel A. Griffith
Keyword(s):  
Spatial Variation ◽  
Spurious Correlation ◽  
Varying Coefficient

scholarly journals Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection

2019 ◽  
Vol 16 (3) ◽  
pp. 339 ◽  
Author(s):  
Frank Osei ◽  
Alfred Stein ◽  
Anthony Ofosu
Keyword(s):  
Drinking Water ◽  
Spatial Variation ◽  
Waste Disposal ◽  
Intestinal Parasites ◽  
Liquid Waste ◽  
Public Health Intervention ◽  
Demographic Factors ◽  
Exceedance Probability ◽  
Varying Coefficient ◽  
Spatially Varying

Understanding the spatially varying effects of demographic factors on the spatio-temporal variation of intestinal parasites infections is important for public health intervention and monitoring. This paper presents a hierarchical Bayesian spatially varying coefficient model to evaluate the effects demographic factors on intestinal parasites morbidities in Ghana. The modeling relied on morbidity data collected by the District Health Information Management Systems. We developed Poisson and Poisson-gamma spatially varying coefficient models. We used the demographic factors, unsafe drinking water, unsafe toilet, and unsafe liquid waste disposal as model covariates. The models were fitted using the integrated nested Laplace approximations (INLA). The overall risk of intestinal parasites infection was estimated to be 10.9 per 100 people with a wide spatial variation in the district-specific posterior risk estimates. Substantial spatial variation of increasing multiplicative effects of unsafe drinking water, unsafe toilet, and unsafe liquid waste disposal occurs on the variation of intestinal parasites risk. The structured residual spatial variation widely dominates the unstructured component, suggesting that the unaccounted-for risk factors are spatially continuous in nature. The study concludes that both the spatial distribution of the posterior risk and the associated exceedance probability maps are essential for monitoring and control of intestinal parasites.

scholarly journals Analysis of spatial variation of credit risk of China listed companies based on spatially varying coefficient logistic models

2021 ◽  
Vol 336 ◽  
pp. 09013
Author(s):  
Ying Du ◽  
Chanchan Wang
Keyword(s):  
Credit Risk ◽  
Spatial Variation ◽  
Logistic Models ◽  
Listed Companies ◽  
Special Treatment ◽  
Varying Coefficient ◽  
Credit Risks ◽  
Industry Type ◽  
Variation Characteristics ◽  
Spatially Varying

Nowadays, since the booming economy of china, the development of financing behaviors, represented by the financial took it such as stocks and bonds, is increasing continuously in our country, meanwhile, it is more and more prominent that the credit risks problems brought by the frequent defaults in credit transactions. Analysis of credit risk characteristics become a very important study topic. Whether A-share listed companies in some provinces in the central and eastern regions of my country being special treatment (ST) are used as a sample to study credit risk. Based on the spatially varying coefficient logistic models, this paper analyzes the spatial variation characteristics of industry type and ownership nature affecting the probability of listed companies being ST. The results show that there is a large spatial variation in the intensity of the influence of these factors on the risk of listed companies being ST.

scholarly journals Poisson-Gamma Mixture Spatially Varying Coefficient Modeling of Small-Area Intestinal Parasites Infection

2018 ◽  
Author(s):  
Frank Badu Osei ◽  
Alfred Stein ◽  
Anthony Ofosu
Keyword(s):  
Drinking Water ◽  
Spatial Variation ◽  
Waste Disposal ◽  
Intestinal Parasites ◽  
Liquid Waste ◽  
Public Health Intervention ◽  
Demographic Factors ◽  
Exceedance Probability ◽  
Varying Coefficient ◽  
Spatially Varying

Understanding the spatially varying effects of demographic factors on the spatio-temporal variation of intestinal parasites infections is important for public health intervention and monitoring. This paper presents a hierarchical Bayesian spatially varying coefficient model to evaluate the effects demographic factors on intestinal parasites morbidities in Ghana. The modeling relied on morbidity data collected by the District Health Information Management Systems. We developed Poisson and Poisson-gamma spatially varying coefficient Models. We used the demographic factors, unsafe drinking water, unsafe toilet and unsafe liquid waste disposal as model covariates. The models were fitted using the Integrated Nested Laplace Approximations (INLA). The overall risk of intestinal parasites infection was estimated to be 10.9 per 100 people with a wide spatial variation in the district-specific posterior risk estimates. Substantial spatial variation of increasing multiplicative effects of unsafe drinking water, unsafe toilet and unsafe liquid waste disposal occurs on the variation of intestinal parasites risk. The structured residual spatial variation widely dominates the unstructured component, suggesting that the unaccounted-for risk factors are spatially continuous in nature. The study concludes that both the spatial distribution of the posterior risk and the associated exceedance probability maps are essential for monitoring and control of intestinal parasites.

Digital representation of spatial variation of multivariate landscape data

2006 ◽  
Vol 7 (2) ◽  
pp. 181-188 ◽  
Author(s):  
A. Altobelli ◽  
E. Bressan ◽  
E. Feoli ◽  
P. Ganis ◽  
F. Martini
Keyword(s):  
Spatial Variation ◽  
Digital Representation

Function of coprophagous beetles (Coleoptera: Scarabaeidae, Geotrupidae, Hydrophilidae) in cattle pastures inferred from pitfall trapping data

2010 ◽  
Vol 27 (2) ◽  
pp. 85-91 ◽  
Author(s):  
Martin Šlachta ◽  
Jan Frelich ◽  
Tomáš Tonka
Keyword(s):  
Seasonal Variation ◽  
Spatial Variation ◽  
Dry Weight ◽  
Seasonal Distribution ◽  
The Other ◽  
Pitfall Trapping ◽  
Other Hand ◽  
Nested Anova ◽  
Species Groups ◽  
Dung Decomposition

Function of coprophagous beetles (Coleoptera: Scarabaeidae, Geotrupidae, Hydrophilidae) in cattle pastures inferred from pitfall trapping dataAn analysis of data on the dry weight biomass of coprophagous beetles in standardized dung (4.5 l) was conducted in order to characterize the spatial and the seasonal distribution of the beetles' biomass in cattle pastures and to elucidate their function in dung decomposition. Nested Anova with factors of farm, site (nested in farm), seasonal period and year was used to evaluate the effect of these factors on the biomass of four functional species groups: the dung dwellers ofScarabaeidae(subfamilyAphodiinae), the dung dwellers ofHydrophilidae, the small tunnellers ofScarabaeidae(subfamilyCoprinae) and the large tunnellers ofGeotrupidae. The spatial variation of biomass (between the sites and the farms) was insignificant (P>0.05) in the two dung-dweller groups and in the large-tunnellers group. On the other hand, a significant (P<0.05) seasonal variation of biomass was found in all but the large tunneller group. In dung dwellers, the spring biomass was formed mainly by two species,Aphodius prodromusandA. sphacelatus. In summer, most of the biomass was accounted for bySphaeridium lunatum, S. scarabaeoidesandA. rufipes. In the two tunneller groups,Onthophagus fracticornis, Geotrupes stercorariusandG. spinigerformed a majority of the biomass in dung.

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