Table 9 Estimated MSE for different estimators at p = 9 and \(\phi =4\).

From: Development of the generalized ridge estimator for the Poisson-Inverse Gaussian regression model with multicollinearity

\(\rho ^2\)

n

PIGMLE

PIGRRE

PIGGRE

MLE

\(\hat{k}_1\)

\(\hat{k}_2\)

\(\hat{k}_3\)

\(\hat{k}_4\)

\(\hat{k}_5\)

\(\hat{K}_1\)

\(\hat{K}_2\)

\(\hat{K}_3\)

\(\hat{K}_4\)

\(\hat{K}_5\)

0.80

30

10.73294

9.45433

8.34504

9.2466

4.77015

3.77006

2.95387

1.04324

0.66517

3.89265

1.13721

75

3.39965

2.8339

2.37349

2.8566

1.67625

1.36618

1.04177

0.28177

0.18911

1.31229

0.31112

150

1.00687

0.91899

0.84481

0.91956

0.57895

0.48226

0.37387

0.10312

0.07488

0.4418

0.11288

200

0.76086

0.71416

0.67315

0.70936

0.45036

0.37757

0.29493

0.08426

0.06381

0.34071

0.09168

300

0.51897

0.49806

0.47875

0.49283

0.32741

0.27601

0.21887

0.06557

0.04934

0.24586

0.0713

400

0.37566

0.3643

0.35349

0.35965

0.23012

0.19321

0.15092

0.04331

0.03603

0.16682

0.0466

0.85

30

19.27733

16.4411

13.97169

15.41655

7.34859

6.03932

4.86817

1.95523

1.39088

6.31112

2.10618

75

3.01251

2.54954

2.17559

2.60826

1.57734

1.28672

0.98978

0.2674

0.16871

1.24286

0.29726

150

1.39509

1.27017

1.16427

1.28516

0.83681

0.6946

0.54567

0.15332

0.0978

0.65557

0.1702

200

0.9971

0.92815

0.86744

0.92901

0.60136

0.49869

0.38857

0.10122

0.06688

0.45827

0.11262

300

0.72715

0.68888

0.65405

0.68541

0.44354

0.36892

0.28808

0.07651

0.0516

0.33138

0.08479

400

0.46915

0.44992

0.43196

0.4442

0.2797

0.23352

0.18064

0.04551

0.03394

0.20371

0.05009

0.90

30

23.48545

20.23299

17.35121

19.28553

8.81518

6.97209

5.49392

2.20602

1.47766

7.3625

2.37001

75

4.88456

4.03043

3.32542

3.97971

2.10156

1.66492

1.2086

0.25931

0.16393

1.62338

0.29102

150

2.0514

1.82449

1.63481

1.87283

1.20509

0.9851

0.7599

0.18865

0.11348

0.94259

0.21218

200

1.5734

1.36041

1.18742

1.40096

0.84245

0.67646

0.50151

0.09732

0.06092

0.62088

0.11088

300

1.0206

0.9376

0.86443

0.93869

0.5753

0.46924

0.35383

0.07563

0.04978

0.4235

0.08522

400

0.72157

0.67685

0.63723

0.67197

0.41639

0.34302

0.26226

0.06088

0.0402

0.30564

0.06817

0.95

30

91.65183

76.54036

63.70994

68.79082

22.89659

18.98429

15.77151

7.78501

5.67074

20.83585

8.24485

75

9.25171

8.01005

6.91761

8.019

4.59294

3.63626

2.73381

0.68391

0.39583

3.75901

0.76761

150

4.25302

3.65305

3.1465

3.78068

2.24924

1.79866

1.35828

0.33327

0.19578

1.79209

0.37437

200

3.16039

2.62687

2.19173

2.71861

1.59826

1.27863

0.95523

0.21441

0.12605

1.2391

0.24246

300

1.8119

1.53173

1.30864

1.57621

0.89114

0.71774

0.52614

0.10264

0.06424

0.66215

0.11651

400

1.34627

1.22863

1.12705

1.23887

0.75511

0.61133

0.45988

0.09511

0.05655

0.5654

0.1084

0.99

30

152.83988

139.29117

127.14329

137.69195

73.0238

58.05439

46.53535

19.79738

13.08846

67.35226

21.25746

75

47.1158

38.7285

31.72315

38.05415

18.62169

14.46648

10.68585

2.9046

1.6622

16.39355

3.22694

150

25.1333

21.27287

17.90344

21.41746

10.35064

7.86377

5.58007

1.06329

0.57424

8.79321

1.21762

200

15.09767

12.36091

9.96464

12.48608

5.6498

4.17964

2.80434

0.37499

0.21025

4.4955

0.43872

300

8.83032

6.92371

5.3008

7.16387

3.54861

2.68545

1.83668

0.25979

0.14606

2.76853

0.30308

400

7.23955

6.10533

5.10174

6.29475

3.30984

2.52143

1.77695

0.29117

0.15611

2.57024

0.33795

  1. Bolded values indicate the lowest MSE.
Back to article page