Table 14 ML estimates (with SE in brackets) of different distributions for bladder cancer data.

From: Properties and inference of the Pareto Lomax distribution with applications to real data

Distribution

Estimates (SE)

OPLx \(\left(\widehat{\alpha},\widehat{\beta},\widehat{\theta},\widehat{\zeta}\right)\)

15.8333(0.9016)

20.0294(0.9991)

4.4334(1.4888)

0.2432(0.0291)

 

FTLLx \(\left(\widehat{\alpha},\widehat{\beta},\widehat{\lambda},\widehat{a},\widehat{b}\right)\)

0.2942(0.0861)

124.6313(170.3355)

0.6259(0.6599)

4.8942(1.2944)

8.1535(1.5286)

TWLx \(\left(\widehat{\alpha},\widehat{\beta},\widehat{\lambda},\widehat{a},\widehat{b}\right)\)

0.1313(0.3090)

12.1876(15.0634)

0.6691(0.4516)

28.7438(125.6130)

1.4625(0.2588)

McLx \(\left(\widehat{\alpha},\widehat{\beta},\widehat{a},\widehat{\eta},\widehat{c}\right)\)

0.8085(3.5544)

11.2929(18.3210)

1.5060(0.2837)

4.1886(26.4337)

2.1046(3.1152)

BELx \(\left(\widehat{\beta},\widehat{\theta},\widehat{\lambda},\widehat{a},\widehat{b}\right)\)

2.6937(4.9196)

1.4469(4.0201)

0.0774(0.1090)

0.5654(0.9943)

2.7032(7.8209)

OLxLL \(\left(\widehat{\alpha},\widehat{\beta},\widehat{a},\widehat{b}\right)\)

2.0701(0.9682)

5.8257(1577.8671)

3.5017(664.3368)

1.4276(0.1779)

 

OEHLLx \(\left(\widehat{\alpha,}\widehat{\lambda},\widehat{a},\widehat{b}\right)\)

1.4334(0.2655)

20.7032(76.9940)

0.1283(0.3765)

9.1700(9.5494)

 

KwLx \(\left(\widehat{\alpha},\widehat{\beta},\widehat{a},\widehat{b}\right)\)

0.3972(2.4596)

12.3381(17.8397)

1.5162(0.2666)

11.8141(86.6921)

 

BXLx \(\left(\widehat{\lambda},\widehat{\theta},\widehat{b}\right)\)

0.2983(0.0511)

1.0201(0.6641)

0.9338(0.2499)

  

Lx \(\left(\widehat{\beta},\widehat{\lambda}\right)\)

121.0226(142.6803)

13.9385(15.3822)

   

W \(\left(\widehat{\beta},\widehat{\lambda}\right)\)

1.0478(0.0675)

0.0938(0.0191)

   

Ga \(\left(\widehat{a},\widehat{b}\right)\)

1.1725(0.1308)

0.1252(0.0173)

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