A Study of Count Regression Models for Mortality Rate
Keyword(s):
This paper discusses how overdispersed count data to be fit. Poisson regression model, Negative Binomial 1 regression model (NEGBIN 1) and Negative Binomial regression 2 (NEGBIN 2) model were proposed to fit mortality rate data. The method used is comparing the values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to find out which method suits the data the most. The results show that the data indeed display higher variability. Among the three models, the model preferred is NEGBIN 1 model.
Selecting the best model to fit the Rainfall Count data Using Some Zero Type models with application
2019 ◽
Vol 11
(2)
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pp. 28-41
2021 ◽
2018 ◽
Vol 15
(3)
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pp. 760-773
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2020 ◽
pp. 64-73