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I 型截尾下污染物负荷的似然推断。

Likelihood inference for pollutant loading under type I censoring.

机构信息

Department of Mathematics, Faculty of Science, Cairo University, Cairo, Egypt.

Department of Statistics, Faculty of Economics and Political Science, Cairo University, Cairo, Egypt.

出版信息

Environ Monit Assess. 2020 Mar 9;192(4):225. doi: 10.1007/s10661-020-8178-5.

Abstract

Exposure to toxic contaminants in the environment harms human and animal health and disturbs the integrity and function of the impacted ecosystem. The impact could be local, regional, and global. The concentration of a toxic substance below or above detection limits or thresholds in environmental samples is frequently recorded as non-detect. We discuss inferences based on exact and modified likelihood methods for the location-scale family with values below the detection limit, and as a special case for the normal distribution with a comparison between the methods. We demonstrate the procedure using Niagara River monitoring data.

摘要

暴露在环境中的有毒污染物会损害人类和动物的健康,扰乱受影响生态系统的完整性和功能。这种影响可能是局部的、区域的和全球性的。环境样本中有毒物质的浓度低于或高于检测限或阈值时,通常记录为未检出。我们讨论了基于确切和修正似然方法的推断,这些方法适用于检测限以下的位置-尺度族,并且作为正态分布的特例,比较了这些方法。我们使用尼亚加拉河监测数据演示了该程序。

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