Fitting Second-Order Parametric Distributions to Data Using Maximum Likelihood Estimation

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).