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Table 3 MLEs and the measures AIC, BIC, HQIC and CAIC

From: The power Lomax distribution with an application to bladder cancer data

Distribution Estimates −Log L AIC BIC HQIC CAIC
Lomax \(\hat{\alpha } = 13.9384\)
\(\hat{\lambda } = 121.023\)
−413.835 831.67 837.37 833.98 831.80
MCLomax \(\hat{\alpha } = 0.8085\)
\(\hat{\beta } = 11.2929\)
\(\hat{a} = 1.5060\)
\(\hat{\eta } = 4.1886\)
\(\hat{c} = 2.1046\)
−409.91 829.82 844.09 835.62 830.14
BLomax \(\hat{\alpha } = 3.9191\)
\(\hat{\beta } = 23.9281\)
\(\hat{a} = 1.5853\)
\(\hat{\eta } = 0.1572\)
−411.743 831.486 842.89 836.12 831.74
KW Lomax \(\hat{\alpha } = 0.3911\)
\(\hat{\beta } = 12.2973\)
\(\hat{a} = 1.5162\)
\(\hat{\eta } = 11.0323\)
−409.94 827.88 839.29 832.52 828.14
Exp Lomax \(\hat{\alpha } = 1.0644\)
\(\hat{\beta } = 0.08\)
\(\hat{\lambda } = 0.006\)
−414.978 835.956 844.512 839.432 836.15
G-lomax \(\hat{\alpha } = 4.754\)
\(\hat{\beta } = 20.581\)
\(\hat{a} = 1.5858\)
−410.081 826.162 834.718 829.638 826.36
TE-Lomax \(\hat{\alpha } = 1.71418\)
\(\hat{\gamma } = 0.05456\)
\(\hat{\lambda } = 0.24401\)
\(\hat{\theta } = 3.33911\)
−410.434 828.868 840.276 833.505 829.13
WLomax \(\hat{\alpha } = 0.25661\)
\(\hat{\beta } = 1.57945\)
\(\hat{a} = 2.42151\)
\(\hat{b} = 1.86389\)
−410.811 829.622 841.03 834.257 829.88
Ext.PLD \(\hat{\alpha } = 0.2387\)
\(\hat{\beta } = 8.04 \times 10^{ - 3}\)
\(\hat{\lambda } = 59.8378\)
−413.835 833.67 842.22 837.14 833.86
ELomax \(\hat{\alpha } = 4.5857\)
\(\hat{\beta } = 24.7414\)
\(\hat{a} = 1.5862\)
−410.07 826.14 834.70 829.62 826.33
Power Lomax \(\hat{\alpha } = 2.07012\)
\(\hat{\beta } = 1.4276\)
\(\hat{\lambda } = 34.8626\)
−409.74 825.48 834.036 828.956 825.67