Nonlinear regression for modeling censored one-dimensional concentration profiles of fugitive dust plumes

被引:8
作者
Johns, CJ
Holmén, BA
Niemeier, DA
Shumway, RH
机构
[1] Univ Colorado, Dept Math, Denver, CO 80217 USA
[2] Univ Calif Davis, Crocker Nucl Lab, Davis, CA 95616 USA
[3] Univ Calif Davis, Dept Civil & Environm Engn, Davis, CA 95616 USA
[4] Univ Calif Davis, Div Stat, Davis, CA 95616 USA
关键词
expectation-maximization algorithm; Gaussian plume equation; lidar;
D O I
10.1198/108571101300325175
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Dust plumes were generated by farm equipment during standard field preparations and harvest operations. Light detection and ranging (lidar) measurements of dust particle concentrations in the plumes were censored by an upper detection limit. The nonstandardized Gaussian curve, with range values as the argument, was used as a model for the one-dimensional plume profile. Maximum likelihood estimates for the Gaussian plume equation were found in order to make inferences concerning plume characteristics.
引用
收藏
页码:99 / 117
页数:19
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