Table 1 Bias’s, MSE’s, AIC’s and ACL’s for MLE’s for \(BS\left(\alpha ,\beta \right).\)

From: Birnbaum Saunders distribution for imprecise data: statistical properties, estimation methods, and real life applications

n

\(BS(\alpha ,\beta )\)

\(\alpha \)

\(\beta \)

AIC

\(\alpha \)

\(\beta \)

Bias

MSE

Bias

MSE

ACL

\(\left(\alpha ,\beta \right)=\left(\mathrm{1.25.5,3}\right)\)

 50

0.0193

0.0188

0.03350

0.0563

9963.393

0.1654

0.5138

 100

0.0088

0.0077

0.0165

0.0273

32,422.27

0.1563

0.3786

 200

0.0045

0.0041

0.0084

0.0141

132,107.5

0.0998

0.2654

 500

0.0018

0.0016

0.0034

0.0060

826,131.3

0.0593

0.1550

\(\left(\alpha ,\beta \right)=\left(\mathrm{0.5,3}\right)\)

 50

0.0039

0.0007

0.0508

0.1292

8980.385

0.0744

0.1795

 100

0.0018

0.0003

0.0239

0.0572

34,746.18

0.0716

0.0167

 200

0.0007

0.0001

0.0125

0.0314

128,830.6

0.0453

0.0960

 500

0.0003

5.16*\({10}^{-5}\)

0.0050

0.0125

810,005.7

0.0283

0.0618

\(\left(\alpha ,\beta \right)=\left(\mathrm{1,3}\right)\)

 50

0.0138

0.0095

0.0428

0.0916

8744.334

0.1340

0.3390

 100

0.0069

0.0048

0.0204

0.0419

36,114.63

0.1169

0.2579

 200

0.0034

00,023

0.0102

0.0208

139,516.5

0.0743

0.1876

 500

0.0013

0.0008

0.0040

0.0080

812,134.2

0.0516

0.1246