Determining the spatial effects of COVID-19 using the spatial panel data model [0.03%]
基于空间面板数据模型的新冠肺炎疫情时空效应研究
Hasraddin Guliyev
Hasraddin Guliyev
This study investigates the propagation power and effects of the coronavirus disease 2019 (COVID-19) in light of published data. We examine the factors affecting COVID-19 together with the spatial effects, and use spatial panel data models ...
Mikyoung Jun,Courtney Schumacher,R Saravanan
Mikyoung Jun
We seek statistical methods to study the occurrence of multiple rain types observed by satellite on a global scale. The main scientific interests are to relate rainfall occurrence with various atmospheric state variables and to study the de...
Using a spatial point process framework to characterize lung computed tomography scans [0.03%]
使用空间点过程框架来描述肺部计算机断层扫描图像
Brian E Vestal,Nichole E Carlson,Raúl San José Estépar et al.
Brian E Vestal et al.
Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming,...
Social Network Spatial Model [0.03%]
社交网络空间模型
Joseph T Ciminelli,Tanzy Love,Tong Tong Wu
Joseph T Ciminelli
Our work is motivated by a desire to incorporate the vast wealth of social network data into the framework of spatial models. We introduce a method for modeling the spatial correlations that exist over a social network. In particular, we mo...
Spatial mapping with Gaussian processes and nonstationary Fourier features [0.03%]
基于高斯过程和非平稳傅里叶特征的时空映射模型
Jean-Francois Ton,Seth Flaxman,Dino Sejdinovic et al.
Jean-Francois Ton et al.
The use of covariance kernels is ubiquitous in the field of spatial statistics. Kernels allow data to be mapped into high-dimensional feature spaces and can thus extend simple linear additive methods to nonlinear methods with higher order i...
A spatially varying change points model for monitoring glaucoma progression using visual field data [0.03%]
一种用于使用视野数据监测青光眼进展的空间变化点过程模型
Samuel I Berchuck,Jean-Claude Mwanza,Joshua L Warren
Samuel I Berchuck
Glaucoma disease progression, as measured by visual field (VF) data, is often defined by periods of relative stability followed by an abrupt decrease in visual ability at some point in time. Determining the transition point of the disease t...
José A Ordoñez,Dipankar Bandyopadhyay,Victor H Lachos et al.
José A Ordoñez et al.
Spatially-referenced geostatistical responses that are collected in environmental sciences research are often subject to detection limits, where the measures are not fully quantifiable. This leads to censoring (left, right, interval, etc), ...
Is a matrix exponential specification suitable for the modeling of spatial correlation structures? [0.03%]
矩阵指数模型规格是否适合空间相关结构的建模？
Magdalena E Strauß,Maura Mezzetti,Samantha Leorato
Magdalena E Strauß
This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to a...
Measuring Aggregation of Events about a Mass Using Spatial Point Pattern Methods [0.03%]
使用空间点过程方法度量关于大规模事件的聚集性
Michael O Smith,Jackson Ball,Benjamin B Holloway et al.
Michael O Smith et al.
We present a methodology that detects event aggregation about a mass surface using 3-dimensional study regions with a point pattern and a mass present. The Aggregation about a Mass function determines aggregation, randomness, or repulsion o...
Y Vandendijck,C Faes,R S Kirby et al.
Y Vandendijck et al.
Obtaining reliable estimates about health outcomes for areas or domains where only few to no samples are available is the goal of small area estimation (SAE). Often, we rely on health surveys to obtain information about health outcomes. Suc...