@misc{eprints86116,
           month = {Maret},
           title = {PERBANDINGAN PERFORMA JAMES-STEIN ESTIMATOR, RIDGE REGRESSION ESTIMATOR, DAN MODIFIED KIBRIA-LUKMAN ESTIMATOR DALAM MENGATASI MULTIKOLINEARITAS  PADA REGRESI POISSON: SIMULASI STUDI },
          author = {ZAMI  M. FIKRI ALYASA ZAM },
         address = {UNIVESITAS LAMPUNG },
       publisher = {FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM },
            year = {2025},
             url = {http://digilib.unila.ac.id/86116/},
        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 }
}