M. FIKRI ALYASA ZAM , ZAMI (2025) PERBANDINGAN PERFORMA JAMES-STEIN ESTIMATOR, RIDGE REGRESSION ESTIMATOR, DAN MODIFIED KIBRIA-LUKMAN ESTIMATOR DALAM MENGATASI MULTIKOLINEARITAS PADA REGRESI POISSON: SIMULASI STUDI. FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM , UNIVESITAS LAMPUNG .
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Abstract
Poisson regression is a statistical method used to analyze data with a response in the form of a count variable. This regression uses the Maximum Likelihood Estimation (MLE) method to estimate model parameters. The purpose of this study is to compare the performance of the Poisson James-Stein Estimator (PJSE), Poisson Ridge Regression Estimator (PRRE), and Poisson Modified Kibria- Lukman Estimator (PMKLE) methods in dealing with multicollinearity using simulated data with n = 20, 40, 60 and 80 in poisson model (p=6) with
| Item Type: | Other |
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| Subjects: | ?? 500 ?? ?? 510 ?? |
| Divisions: | ?? matematika ?? |
| Depositing User: | 2308168512 . Digilib |
| Date Deposited: | 16 Apr 2025 10:37 |
| Last Modified: | 16 Apr 2025 10:37 |
| URI: | http://digilib.unila.ac.id/id/eprint/86116 |
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