Results 31 to 40 of about 12,857 (287)
Comparison of Test Statistic for Zero-Inflated Negative Binomial against Zero-Inflated Poisson Model
Indian Journal of Science and Technology, 2015 In this study, the existence of score test and alternative tests were studied for testing the overdispersion parameter after including covariates in ZINB against ZIP models. The power of the three tests for different degrees of overdispersion parameter and various sample sizes were also obtained through Monte Carlo simulation.
B. Muniswamy +2 more
openaire +3 more sources
, 2023 Priors for the logistic regression model, the zero-inflated negative binomial model, and the negative binomial model.
Clara Pencer (9459661) +5 more
core +1 more source
Multiple inflated negative binomial regression for correlated multivariate count data
Dependence Modeling, 2022 This article aims to provide a method of regression for multivariate multiple inflated count responses assuming the responses follow a negative binomial distribution.
Mathews Joseph +3 more
doaj +1 more source
Using observation-level random effects to model overdispersion in count data in ecology and evolution [PDF]
, 2014 Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated) data, or an excess frequency of zeroes (zero-inflation).
Xavier A. Harrison, Harrison, XA
core +1 more source
, 2023 Summary of model fits for the logistic regression model, the zero-inflated negative binomial model, and the negative binomial model.
Clara Pencer (9459661) +5 more
core +1 more source
Journal of Physics: Conference Series, 2017 Tetanus Neonatorum is an infectious disease that can be prevented by immunization. The number of Tetanus Neonatorum cases in East Java Province is the highest in Indonesia until 2015. Tetanus Neonatorum data contain over dispersion and big enough proportion of zero-inflation.
Luthfatul Amaliana +2 more
openaire +1 more source
Zero-inflated negative binomial regression.
, 2018 Zero-inflated negative binomial regression.
Nick Scott (837353) +5 more
core +1 more source
Bayesian variable selection in modelling geographical heterogeneity in malaria transmission from sparse data : an application to Nouna Health and Demographic Surveillance System (HDSS) data, Burkina Faso [PDF]
, 2015 Quantification of malaria heterogeneity is very challenging, partly because of the underlying characteristics of mosquitoes and also because malaria is an environmentally driven disease.
Diboulo, Eric +11 more
core +1 more source
Journal of New Theory, 2021 The Poisson regression model is widely used for count data. This model assumes equidispersion. In practice, equidispersion is seldom reflected in data. However, in real-life data, the variance usually exceeds the mean.
Burcu Durmuş, Öznur İşçi Güneri
doaj +1 more source
Zero-inflated negative binomial multivariable model of number of decayed teeth (DT) (N = 312).
, 2016 Zero-inflated negative binomial multivariable model of number of decayed teeth (DT) (N = 312).
Stephen S. Dominy (549343) +9 more
core +1 more source