creators_name: M. FIKRI ALYASA ZAM , ZAMI 
creators_id: 2117031016
type: other
datestamp: 2025-04-16 10:37:30
lastmod: 2025-04-16 10:37:30
metadata_visibility: show
title: PERBANDINGAN PERFORMA JAMES-STEIN ESTIMATOR, RIDGE REGRESSION ESTIMATOR, DAN MODIFIED KIBRIA-LUKMAN ESTIMATOR DALAM MENGATASI MULTIKOLINEARITAS  PADA REGRESI POISSON: SIMULASI STUDI 
ispublished: pub
subjects: 500
subjects: 510
full_text_status: restricted
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 
date: 2025-03-24
date_type: published
publisher: FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM 
place_of_pub: UNIVESITAS LAMPUNG 
citation:   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 .     
document_url: http://digilib.unila.ac.id/86116/1/ABSTRAK.pdf
document_url: http://digilib.unila.ac.id/86116/2/SKRIPSI%20FULL.pdf
document_url: http://digilib.unila.ac.id/86116/3/SKRIPSI%20TANPA%20BAB%20PEMBAHASAN.pdf