PERBANDINGAN REGRESI BINOMIAL NEGATIF DAN REGRESI GENERALISASI POISSON DALAM MENGATASI OVERDISPERSI (Studi Kasus: Jumlah Tenaga Kerja Usaha Pencetak Genteng di Br. Dukuh, Desa Pejaten)
| Main Authors: | KESWARI, NI MADE RARA; Faculty of Mathematics and Natural Sciences, Udayana University, SUMARJAYA, I WAYAN; Faculty of Mathematics and Natural Sciences, Udayana University, SUCIPTAWATI, NI LUH PUTU; Faculty of Mathematics and Natural Sciences, Udayana University |
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| Format: | Article application/pdf eJournal |
| Bahasa: | ind |
| Terbitan: |
E-Jurnal Matematika
, 2015
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| Subjects: | |
| Online Access: |
http://ojs.unud.ac.id/index.php/mtk/article/view/12001 |
Daftar Isi:
- Poisson regression is a nonlinear regression that is often used to model count response variable and categorical, interval, or count regressor. This regression assumes equidispersion, i.e., the variance equals the mean. However, in practice, this assumption is often violated. One of this violation is overdispersion in which the variance is greater than the mean. There are several methods to overcome overdispersion. Two of these methods are negative binomial regression and generalized Poisson regression. In this research, binomial negative regression and generalized Poisson regression statistically equally good in handling overdispersion.