PERBANDINGAN REGRESI ZERO INFLATED POISSON (ZIP) DAN REGRESI ZERO INFLATED NEGATIVE BINOMIAL (ZINB) PADA DATA OVERDISPERSION (Studi Kasus: Angka Kematian Ibu di Provinsi Bali)
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چکیده
منابع مشابه
Zero-Inflated Poisson and Zero-Inflated Negative Binomial Models Using the COUNTREG Procedure
Real-life count data are frequently characterized by overdispersion and excess zeros. Zero-inflated count models provide a parsimonious yet powerful way to model this type of situation. Such models assume that the data are a mixture of two separate data generation processes: one generates only zeros, and the other is either a Poisson or a negative binomial data-generating process. The result of...
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Background: The number of failed courses and semesters in students are indicatorsof their performance. These amounts have zero inflated (ZI) distributions. Using ZI Poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. This study aims at to investigate the important factors related to the educational performance of ...
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Hall (2000) has described zero-inflated Poisson and binomial regression models that include random effects to account for excess zeros and additional sources of heterogeneity in the data. The authors of the present paper propose a general score test for the null hypothesis that variance components associated with these random effects are zero. For a zero-inflated Poisson model with random inter...
متن کاملzero inflated poisson and negative binomial regression models: application in education
background: the number of failed courses and semesters in students are indicatorsof their performance. these amounts have zero inflated (zi) distributions. using zi poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. this study aims at to investigate the important factors related to the educational performance of ...
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ژورنال
عنوان ژورنال: E-Jurnal Matematika
سال: 2016
ISSN: 2303-1751
DOI: 10.24843/mtk.2016.v05.i04.p132