Environmental risk assessment of emerging contaminants using degradation data

DOI10.1007/s13253-018-0326-9zbMath1426.62348OpenAlexW2801766604WikidataQ129835027 ScholiaQ129835027MaRDI QIDQ1618102

Zhi-Sheng Ye, Lanqing Hong, Ran Ling

Publication date: 13 November 2018

Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13253-018-0326-9

zbMATH Keywords

stochastic processinterval estimationmulti-dimensional degradation modelrisk indicator

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Applications of statistics to environmental and related topics (62P12) Markov processes: estimation; hidden Markov models (62M05)

Related Items (2)

Comparing coefficients across subpopulations in Gaussian mixture regression models ⋮ Inverse Gaussian processes with correlated random effects for multivariate degradation modeling

Cites Work

• Unnamed Item
• Unnamed Item
• Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting
• Failure inference from a marker process based on a bivariate Wiener model
• Empirical evaluation of sufficient similarity in dose-response for environmental risk assessment of chemical mixtures
• Generalized Confidence Intervals
• Hitting Lines with Two-Dimensional Brownian Motion
• When is Acceleration Unnecessary in a Degradation Test?
• Fiducial Generalized Confidence Intervals

This page was built for publication: Environmental risk assessment of emerging contaminants using degradation data