PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON
| Main Authors: | PRADAWATI, PUTU SUSAN; Faculty of Mathematics and Natural Sciences, Udayana University, SUKARSA, KOMANG GDE; Faculty of Mathematics and Natural Sciences, Udayana University, SRINADI, I GUSTI AYU MADE; Faculty of Mathematics and Natural Sciences, Udayana University |
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| Format: | Article application/pdf eJournal |
| Bahasa: | ind |
| Terbitan: |
E-Jurnal Matematika
, 2013
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| Subjects: | |
| Online Access: |
http://ojs.unud.ac.id/index.php/mtk/article/view/6285 |
Daftar Isi:
- Poisson regression was used to analyze the count data which Poisson distributed. Poisson regression analysis requires state equidispersion, in which the mean value of the response variable is equal to the value of the variance. However, there are deviations in which the value of the response variable variance is greater than the mean. This is called overdispersion. If overdispersion happens and Poisson Regression analysis is being used, then underestimated standard errors will be obtained. Negative Binomial Regression can handle overdispersion because it contains a dispersion parameter. From the simulation data which experienced overdispersion in the Poisson Regression model it was found that the Negative Binomial Regression was better than the Poisson Regression model.