E-Jurnal Matematika
Vol 2 No 2 (2013)

PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON

PUTU SUSAN PRADAWATI (Faculty of Mathematics and Natural Sciences, Udayana University)
KOMANG GDE SUKARSA (Faculty of Mathematics and Natural Sciences, Udayana University)
I GUSTI AYU MADE SRINADI (Faculty of Mathematics and Natural Sciences, Udayana University)



Article Info

Publish Date
02 Sep 2013

Abstract

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.

Copyrights © 2013






Journal Info

Abbrev

mtk

Publisher

Subject

Mathematics

Description

E-Jurnal Matematika merupakan salah satu jurnal elektronik yang ada di Universitas Udayana, sebagai media komunikasi antar peminat di bidang ilmu matematika dan terapannya, seperti statistika, matematika finansial, pengajaran matematika dan terapan matematika dibidang ilmu lainnya. Jurnal ini lahir ...