Population Size Estimation using Zero-truncated Poisson Regression with Measurement Error [0.03%]
具有测量误差的零截断泊松回归人口规模估计方法研究
Wen-Han Hwang,Jakub Stoklosa,Ching-Yun Wang
Wen-Han Hwang
Population size estimation is an important research field in biological sciences. In practice, covariates are often measured upon capture on individuals sampled from the population. However, some biological measurements, such as body weight...
A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA [0.03%]
美国空气污染暴露与COVID-19死亡率的时空分析展望
Sounak Chakraborty,Tanujit Dey,Yoonbae Jun et al.
Sounak Chakraborty et al.
The world is experiencing a pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The USA is also suffering from a catastrophic death toll from COVID-19. Several studies are providing prelimin...
Roman Flury,Reinhard Furrer
Roman Flury
We discuss the experiences and results of the AppStatUZH team's participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each o...
Denis Allard,Lucia Clarotto,Thomas Opitz et al.
Denis Allard et al.
We discuss the methods and results of the RESSTE team in the competition on spatial statistics for large datasets. In the first sub-competition, we implemented block approaches both for the estimation of the covariance parameters and for pr...
Statistical downscaling with spatial misalignment: Application to wildland fire PM2.5 concentration forecasting [0.03%]
空间错位下的统计降尺度方法及其在野火PM2.5浓度预报中的应用
Suman Majumder,Yawen Guan,Brian J Reich et al.
Suman Majumder et al.
Fine particulate matter, PM2.5, has been documented to have adverse health effects and wildland fires are a major contributor to PM2.5 air pollution in the US. Forecasters use numerical models to predict PM2.5 concentrations to warn the pub...
Semiparametric Mixed-Effects Ordinary Differential Equation Models with Heavy-Tailed Distributions [0.03%]
具有重尾分布的半参数混合效应常微分方程模型
Baisen Liu,Liangliang Wang,Yunlong Nie et al.
Baisen Liu et al.
Ordinary differential equation (ODE) models are popularly used to describe complex dynamical systems. When estimating ODE parameters from noisy data, a common distribution assumption is using the Gaussian distribution. It is known that the ...
Bringing It All Together: Multi-species Integrated Population Modelling of a Breeding Community [0.03%]
统合之法：繁殖群落中多物种综合种群模型分析
José J Lahoz-Monfort,Michael P Harris,Sarah Wanless et al.
José J Lahoz-Monfort et al.
Integrated population models (IPMs) combine data on different aspects of demography with time-series of population abundance. IPMs are becoming increasingly popular in the study of wildlife populations, but their application has largely bee...
A Test of Positive Association for Detecting Heterogeneity in Capture for Capture-Recapture Data [0.03%]
用于捕获重 capture-recapture 数据检测捕获异质性的正向关联检验
Anita Jeyam,Rachel S McCrea,Thomas Bregnballe et al.
Anita Jeyam et al.
The Cormack-Jolly-Seber (CJS) model assumes that all marked animals have equal recapture probabilities at each sampling occasion, but heterogeneity in capture often occurs and should be taken into account to avoid biases in parameter estima...
Matthew J Heaton,Abhirup Datta,Andrew O Finley et al.
Matthew J Heaton et al.
The Gaussian process is an indispensable tool for spatial data analysts. The onset of the "big data" era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alter...
Jiguo Cao,Kunlaya Soiaporn,Raymond J Carroll et al.
Jiguo Cao et al.
We propose a copula-based approach for analyzing functional data with correlated multiple functional outcomes exhibiting heterogeneous shape characteristics. To accommodate the possibly large number of parameters due to having several funct...