PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON
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Authors:
PUTU SUSAN PRADAWATI, KOMANG GDE SUKARSA, I GUSTI AYU MADE SRINADI
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.”
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https://jurnal.harianregional.com/mtk/full-6285
Published
2013-09-02
How To Cite
PRADAWATI, PUTU SUSAN; SUKARSA, KOMANG GDE; SRINADI, I GUSTI AYU MADE. PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON.E-Jurnal Matematika, [S.l.], v. 2, n. 2, p. 6-10, sep. 2013. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-6285. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/MTK.2013.v02.i02.p031.
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Issue
Vol 2 No 2 (2013)
Section
Articles
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This work is licensed under a Creative Commons Attribution 4.0 International License
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