An empirical multivariate log-normal distribution representing uncertainty of biokinetic parameters for 137Cs.
A simplified biokinetic model for (137)Cs has six parameters representing transfer of material to and from various compartments. Using a Bayesian analysis, the joint probability distribution of these six parameters is determined empirically for two cases with quite a lot of bioassay data. The distribution is found to be a multivariate log-normal. Correlations between different parameters are obtained. The method utilises a fairly large number of pre-determined forward biokinetic calculations, whose results are stored in interpolation tables. Four different methods to sample the multidimensional parameter space with a limited number of samples are investigated: random, stratified, Latin Hypercube sampling with a uniform distribution of parameters and importance sampling using a lognormal distribution that approximates the posterior distribution. The importance sampling method gives much smaller sampling uncertainty. No sampling method-dependent differences are perceptible for the uniform distribution methods.
Miller
G
G
Los Alamos National Laboratory, Los Alamos, NM, USA. guthriemiller@gmail.com
Melo
D
D
Martz
H
H
Bertelli
L
L
D000328:Adult; D000465:Algorithms; D001499:Bayes Theorem; D001938:Brazil; D002588:Cesium Radioisotopes / Q000008:administration & dosage / Q000493:pharmacokinetics*; D002648:Child; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D008956:Models, Chemical; D015233:Models, Statistical; D016011:Normal Distribution; D011829:Radiation Dosage; D011832:Radiation Injuries / Q000378:metabolism; D016008:Statistical Distributions; D035501:Uncertainty
D002588:Cesium Radioisotopes