Literature DB >> 32152889

Likelihood inference for pollutant loading under type I censoring.

Hossam M Hassan1, Abdel H El-Shaarawi2.   

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.

Entities:  

Keywords:  EM algorithm; Likelihood; Modified likelihood; Toxic contaminants; Type I censoring; Water quality

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Year:  2020        PMID: 32152889     DOI: 10.1007/s10661-020-8178-5

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  2 in total

1.  Estimating the mean and standard deviation from a censored normal sample.

Authors:  M L Tiku
Journal:  Biometrika       Date:  1967-06       Impact factor: 2.445

2.  Iterative maximum-likelihood estimation of the parameters of normal populations from singly and doubly censored samples.

Authors:  H L Harter; A H Moore
Journal:  Biometrika       Date:  1966-06       Impact factor: 2.445

  2 in total

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