Adam Elder,Youyi Fong
Adam Elder
We introduce a new type of threshold regression models called upper hinge models. Under this type of threshold models, there only exists an association between the predictor of interest and the outcome when the predictor is less than some t...
Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model [0.03%]
使用自回归隐马尔可夫模型对安达卢西亚西部的滨螺进行建模
Jordan Aron,Paul S Albert,Matthew O Gribble
Jordan Aron
Dinophysis spp. can produce diarrhetic shellfish toxins (DST) including okadaic acid and dinophysistoxins, and some strains can also produce non-diarrheic pectenotoxins. Although DSTs are of human health concern and have motivated environme...
A Bayesian mixture model for missing data in marine mammal growth analysis [0.03%]
贝叶斯混合模型在海洋哺乳动物增长分析中缺失数据处理中的应用
Mary E Shotwell,Wayne E McFee,Elizabeth H Slate
Mary E Shotwell
Much of what is known about bottle nose dolphin (Tursiops truncatus) anatomy and physiology is based on necropsies from stranding events. Measurements of total body length, total body mass, and age are used to estimate growth. It is more fe...
Resampling-based multiple comparison procedure with application to point-wise testing with functional data [0.03%]
一种基于重抽样的多重比较方法及其在功能数据分析中的应用
Olga A Vsevolozhskaya,Mark C Greenwood,Scott L Powell et al.
Olga A Vsevolozhskaya et al.
In this paper we describe a coherent multiple testing procedure for correlated test statistics such as are encountered in functional linear models. The procedure makes use of two different p-value combination methods: the Fisher combination...
A model-based approach for imputing censored data in source apportionment studies [0.03%]
源归因研究中基于模型的阙值数据处理方法
Jenna R Krall,Charles H Simpson,Roger D Peng
Jenna R Krall
Sources of particulate matter (PM) air pollution are generally inferred from PM chemical constituent concentrations using source apportionment models. Concentrations of PM constituents are often censored below minimum detection limits (MDL)...
A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates [0.03%]
具有空间和时空协变量的空气污染的灵活时空模型
Johan Lindström,Adam A Szpiro,Paul D Sampson et al.
Johan Lindström et al.
The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-te...
Rc Puett,Ab Lawson,Ab Clark et al.
Rc Puett et al.
Many statistical tests have been developed to assess the significance of clusters of disease located around known sources of environmental contaminants, also known as focused disease clusters. The majority of focused-cluster tests were desi...
Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data [0.03%]
不规则间隔的气溶胶光学厚度数据的时空建模方法研究
Jacob J Oleson,Naresh Kumar,Brian J Smith
Jacob J Oleson
Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size...
Space-time stick-breaking processes for small area disease cluster estimation [0.03%]
时空逐段过程在小区域疾病群估计中的应用
Md Monir Hossain,Andrew B Lawson,Bo Cai et al.
Md Monir Hossain et al.
We propose a space-time stick-breaking process for the disease cluster estimation. The dependencies for spatial and temporal effects are introduced by using space-time covariate dependent kernel stick-breaking processes. We compared this mo...
Infant Mortality and Social Environment in Georgia: An application of hotspot detection and prioritization [0.03%]
格鲁吉亚婴儿死亡率与社会环境：热点检测与优先级划分之应用
Tse-Chuan Yang,Brian McManus
Tse-Chuan Yang
Recent years have witnessed the growth of new information technologies and their applications to various disciplines. The goal of this paper is to demonstrate how the two innovative methods, upper level set scan (ULS) hotspot detection and ...