Key points are not available for this paper at this time.
Second-order random variables, i.e., parametric random variables with uncertain parameters, give risk assessors a way to distinguish and represent both the variability and the uncertainty in an exposure variable. In this manuscript, we explore ways to fit second order random variables to data using maximum likelihood estimation (MLE).
Burmaster et al. (Wed,) studied this question.