Bootstrap simulation for quantification of uncertainty in risk assessment
2007
Chang, K.Y. (Ministry of Agriculture and Forestry, Gwacheon, Republic of Korea) | Hong, K.O. (Ministry of Agriculture and Forestry, Gwacheon, Republic of Korea) | Pak, S.I. (Kangwon National University, Chuncheon, Republic of Korea), E-mail: paksi@kangwon.ac.kr
The choice of input distribution in quantitative risk assessments modeling is of great importance to get unbiased overall estimates, although it is difficult to characterize them in situations where data available are too sparse or small. The present study is particularly concerned with accommodation of uncertainties commonly encountered in the practice of modeling. The authors applied parametric and non-parametric bootstrap simulation methods which consist of re-sampling with replacement, in together with the classical Student-t statistics based on the normal distribution.
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