On the Mean Residual Life Function and Stress and Strength Analysis under Different Loss Function for Lindley Distribution

Table 13

Bayes estimator and posterior risk of stress and strength parameter under SLLF.

𝑛	UP			JP
𝑅	0.026364	0.0604	0.998771	0.026364	0.0604	0.998771
20, 40	0.027033 (0.11001)	0.061970 (0.077534)	0.998762 (1.4526∗10^−7)	0.026509 (0.109867)	0.060832 (0.077376)	0.998728 (1.40892∗10^−7)
60, 80	0.026465 (0.042628)	0.060684 (0.029901)	0.998756 (6.24387∗10^−8)	0.026398 (0.042621)	0.060480 (0.029899)	0.998749 (6.20736∗10^−8)
80, 100	0.026398 (0.032862)	0.060436 (0.023035)	0.998754 (4.91134∗10^−8)	0.026363 (0.032859)	0.060372 (0.023033)	0.998749 (4.89283∗10^−8)
80, 60	0.026109 (0.042241)	0.059822 (0.029329)	0.998735 (6.7568∗10^−8)	0.026243 (0.042241)	0.060138 (0.029323)	0.998738 (6.75607∗10^−8)
100, 60	0.026071 (0.038466)	0.059625 (0.026609)	0.998733 (6.33217∗10^−8)	0.026262 (0.038458)	0.060068 (0.026605)	0.99874 (6.32621∗10^−8)
𝑛	LMP			GP
𝑅	0.026364	0.0604	0.998771	0.026364	0.0604	0.998771
20, 40	0.027104 (0.109771)	0.062474 (0.077367)	0.99874 (1.40666∗10^−7)	0.026511 (0.109817)	0.061372 (0.077337)	0.99871 (1.37639∗10^−7)
60, 80	0.026487 (0.042620)	0.060853 (0.029893)	0.998748 (6.20223∗10^−8)	0.026392 (0.042619)	0.060718 (0.029804)	0.998743 (6.16733∗10^−8)
80, 100	0.026414 (0.032860)	0.060626 (0.023029)	0.998748 (4.88632∗10^−8)	0.026358 (0.032858)	0.060559 (0.023030)	0.998745 (4.8698∗10^−8)
80, 60	0.026123 (0.042240)	0.060133 (0.029322)	0.998729 (6.71435∗10^−8)	0.026227 (0.042235)	0.060425 (0.029307)	0.998733 (6.7069∗10^−8)
100, 60	0.026081 (0.038459)	0.059934 (0.026602)	0.998728 (6.29729∗10^−8)	0.026244 (0.038455)	0.060347 (0.026580)	0.998736 (6.24607∗10^−8)