Simulation study using Gamma distribution: Next assume , i.e., the gamma distribution, where , and as the shape, scale and location parameters respectively. For simplicity assume , , then one can easily see that =E(X), for which the best estimate is . Considering the bounded SEL and LINEX risk problem for the gamma distribution the corresponding optimal sample sizes, are respectively given by  and  (with ). Thus with unknown one may solve both these bounded risk problems using any one of the sequential analysis methods discussed earlier.

Simulation study using Extreme Value Distribution: Finally consider as the Extreme Value Distribution (EVD) with m as its location parameter and s as the scale parameter. We know the estimate of is , where , while that of is . Hence the SEL bounded risk optimal sample size is . In case one considers the LINEX loss function, then the optimal sample size for the bounded LINEX loss risk is , when  and . Hence to find the optimal estimate of , with unknown s, both these bounded risk problems may be solved employing any one of the sequential sampling methods discussed. Furthermore this estimate of may be used to calculate E(X). Hence one first finds the bounded risk estimate of and then calculates E(X) using , where , is the estimate of found using any one of the sequential sampling plans.