PENANGANAN OVERDISPERSI PADA MODEL REGRESI POISSON MENGGUNAKAN MODEL REGRESI BINOMIAL NEGATIF

Simarmata, Rio Tongaril and Ispriyanti, Dwi (2011) PENANGANAN OVERDISPERSI PADA MODEL REGRESI POISSON MENGGUNAKAN MODEL REGRESI BINOMIAL NEGATIF. Media Statistika, 4 (2). pp. 95-104. ISSN 1979-3693

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Abstract

Poisson regression is the most popular tool for modeling the relationship between a discrete data in the response variable and a set of predictors with continue, discrete, categoric or mix data. Response variable with discrete data, however, may overdispersed or underdispersed, not conductive to Poisson regression which assumed that the mean value equals to variance (equidispersed). One of the model that be used to overdispersed the discrete data is a regression model based on mixture distribution namely Poisson-gamma mixture which result negative binomial distribution. This regression model usually known as binomial negative regression. Using Generalized Linier Model (GLM) approach, the given model, parameter estimate, diagnostics, and interpretation of negative binomial regression can be determined.

Item Type:Article
Uncontrolled Keywords:Negative Binomial Distribution, Dispersion, Generalized Linier Model
Subjects:Q Science > Q Science (General)
Divisions:Faculty of Science and Mathematics > Department of Statistics
ID Code:33673
Deposited By:Mr Hasbi Yasin
Deposited On:22 Feb 2012 12:21
Last Modified:22 Feb 2012 12:21

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