Results 1 to 10 of about 45,763 (274)
Using observation-level random effects to model overdispersion in count data in ecology and evolution [PDF]
PeerJ, 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
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Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research [PDF]
BMC Medical Research Methodology, 2016 Background In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework.
Miguel Angel Luque-Fernandez +5 more
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A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution [PDF]
PeerJ, 2015 Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors.
Xavier A. Harrison
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Hierarchical Generalized Linear Models: The R Package HGLMMM [PDF]
Journal of Statistical Software, 2011 The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution.
Marek Molas, Emmanuel Lesaffre
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Barekeng, 2023 The research began with calculating the value of multidimensional poverty at the district level in West Java Province from SUSENAS 2021. The calculation of multidimensional poverty was based on individuals in each district or city household.
Satria June Adwendi +2 more
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New statistical process control charts for overdispersed count data based on the Bell distribution [PDF]
Anais da Academia Brasileira de Ciências, 2023 Poisson distribution is a popular discrete model used to describe counting information, from which traditional control charts involving count data, such as the c and u charts, have been established in the literature.
LAION L. BOAVENTURA +4 more
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Monitoring overdispersed process in clinical laboratories using control charts
Dyna, 2022 Overdispersion is a phenomenon that generally occurs in the analysis of large sample sizes. In discrete data analysis, it refers to the presence of a variation higher than that implied by a reference Binomial or Poisson distributions.
José I. Valdés-Manuel +1 more
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Overdispersed gene expression in schizophrenia [PDF]
npj Schizophrenia, 2020 Abstract Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants a daunting task.
Guangzao Huang +4 more
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Frontiers in Public Health, 2022 IntroductionAn excess in the daily fluctuation of COVID-19 in hospital admissions could cause uncertainty and delays in the implementation of care interventions.
Danila Azzolina +7 more
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Overdispersed variational autoencoders [PDF]
2017 International Joint Conference on Neural Networks (IJCNN), 2017 The ability to fit complex generative probabilistic models to data is a key challenge in AI. Currently, variational methods are popular, but remain difficult to train due to high variance of the sampling methods employed. We introduce the overdispersed variational autoencoder and overdispersed importance weighted autoencoder, which combine ...
Harshil Shah +2 more
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