Algorithm 1.

Step 1: Generate sample from the Birnbaum-Saunders distribution

Step 2: Compute A, B, C, $S_1$, $S_2$

Step 3: At the $m$ step

(a) Simulate $T~t(n-1)$ and compute $R_{\beta }$ using Eq. (3)

(b) If $R_{\beta }<0$, resimulate $T\sim t(n-1)$

(c) Simulate $V\sim {\chi }^2(n)$ and compute $R_{\alpha }$ using Eq. (4)

(d) Compute $R_{\theta }$ using Eq. (5)

Step 4: Repeat step 3, a total M times and obtain an array of $R_{\theta }$’s

Step 5: Compute $L_{\theta .GCI}=R_{\theta }(\gamma /2)$ and $U_{\theta .GCI}=R_{\theta }(1-\gamma /2)$