Award Date
1-1-2002
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematical Sciences
First Committee Member
Malwane Ananda
Number of Pages
37
Abstract
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.
Keywords
Assessment; Confidence; Exposure; Intervals; Risk
Controlled Subject
Statistics
File Format
File Size
921.6 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Permissions
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Repository Citation
Kirkham, Mark S, "Confidence intervals for exposure risk assessment" (2002). UNLV Retrospective Theses & Dissertations. 1431.
http://dx.doi.org/10.25669/gzag-edmj
Rights
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