Modeling the US national distribution of waterborne pathogen concentrations with application to Cryptosporidium parvum -: art. no. 1235

被引:20
作者
Crainiceanu, CM
Stedinger, JR
Ruppert, D
Behr, CT
机构
[1] Cornell Univ, Dept Stat Sci, Ithaca, NY 14853 USA
[2] Cornell Univ, Sch Civil & Environm Engn, Ithaca, NY 14853 USA
[3] Cornell Univ, Sch Operat Res & Ind Engn, Ithaca, NY 14853 USA
[4] eDesign Dynam LLC, W New York, NJ 07093 USA
关键词
Bayesian analysis; Markov Chain Monte Carlo; waterborne pathogens; Cryptosporidium parvum; generalized linear mixed model;
D O I
10.1029/2002WR001664
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper provides a general statistical methodology for modeling environmental pathogen concentrations in natural waters. A hierarchical model of pathogen concentrations captures site and regional random effects as well as random laboratory recovery rates. Recovery rates were modeled by a generalized linear mixed model. Two classes of pathogen concentration models are differentiated according to their ultimate purpose: water quality prediction or health risk analysis. A fully Bayesian analysis using Markov chain Monte Carlo (MCMC) simulation is used for statistical inference. The applicability of this methodology is illustrated by the analysis of a national survey of Cryptosporidium parvum concentrations, in which 93% of the observations were zero counts.
引用
收藏
页码:SWC21 / SWC215
页数:15
相关论文
共 58 条
[1]  
[Anonymous], 2000, C&H TEXT STAT SCI
[2]  
[Anonymous], RED RISK SETT PRIOR
[3]  
[Anonymous], 2002, CASE STUDIES BAYESIA
[4]  
[Anonymous], 2002, CASE STUDIES BAYESIA
[5]  
[Anonymous], CRYPTOSPORIDIUM CRYP
[6]  
Atherholt TB, 1998, J AM WATER WORKS ASS, V90, P66
[7]   A Markov chain Monte Carlo scheme for parameter estimation and inference in conceptual rainfall-runoff modeling [J].
Bates, BC ;
Campbell, EP .
WATER RESOURCES RESEARCH, 2001, 37 (04) :937-947
[8]  
BEHR CT, 2001, THESIS CORNELL U ITH
[9]  
BEST NG, 2002, CASE STUDIES BAYESIA, V5, P153
[10]   APPROXIMATE INFERENCE IN GENERALIZED LINEAR MIXED MODELS [J].
BRESLOW, NE ;
CLAYTON, DG .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1993, 88 (421) :9-25