Table 14 The ML estimates and SEs of the parameters of the EAPLL model and other models for carbon fibers data.

From: Properties, estimation, and applications of the extended log-logistic distribution

Models

Estimates and SEs

EAPLL(\(\beta , \lambda , \theta , \alpha \))

0.3350

0.3309

7.2540

5.4004

  

(0.0942)

(0.0524)

(1.4377)

(12.9625)

  

KwLL(\(a, b, \alpha , \beta \))

0.3467

1.0474

3.4115

7.2673

  

(0.3235)

(1.1470)

(0.7526)

(4.9640)

  

AWLL(\(\alpha ,\lambda ,a,b,c,d\))

2.0217

14.5887

73.9629

1.3814

13.3971

1.3814

(77.9242)

(1954.4477)

(25467.6279)

(53.2548)

(16714.6989)

(53.2117)

EOWLL(\(\alpha , \beta , \lambda , \tau \))

1.4139

0.1386

4.3838

2.1496

  

(0.1652)

(0.0613)

(0.1890)

(1.0205)

  

WGLL(\(\alpha , a, \beta \))

1.0362

0.4971

3.5673

   

(0.8590)

(0.2432)

(2.0896)

   

ExLL(\(\alpha , \beta , \lambda \))

2.1198

3.4385

128.5259

   

(0.7267)

(0.3693)

(76.2269)

   

APLL(\(\lambda , \theta , \alpha \))

2.4831

4.1171

1.0510

   

(1.4920)

(0.3454)

(5.1946)

   

ELL(\(\lambda , \beta , \theta \))

3.3710

7.3389

0.3370

   

(0.2114)

(1.3751)

(0.0925)

   

LL(\(\alpha , \beta \))

2.4982

4.1178

    

(0.1054)

(0.3441)

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