Confidence intervals for exposure risk assessment

The problem of estimating exposure to a pollutant involves estimation of chemical intake Q. Typically, Q has the form Q = q11q12&cdots;q 1r1/q211q22 &cdots;q2r2t where all thetaij's are unknown means of certain random variables. In assessing the risk to human health from exposure to the pollutant of concern, a confidence interval estimate of Q is needed. In the case of independent normal random variables, point estimates and certain types of interval estimates of a product of several parameters exist in the literature, but not for a ratio of products. In many situations, lot of prior knowledge is available regarding the random variables corresponding to these parameters. In the case of independent normal random variables, we look at this problem from a Bayesian approach, and show how to incorporate prior knowledge to calculate confidence interval for Q. In situations with no prior knowledge, generalized Bayes approach with noninformative priors can be used. Several real and simulated examples are provided to demonstrate the proposed procedures.

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mathematical Sciences

Grantor dc:publisher

University of Nevada, Las Vegas

Year

2002

Author dc:creator

• Kirkham, Mark S

Contributors dc:contributor

• Malwane Ananda

Statement dc:rights

• IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English

Identifier

https://oasis.library.unlv.edu/rtds/1431

OAI identifier oai:identifier

oai:oasis.library.unlv.edu:rtds-2430