Results 1 to 10 of about 18,948 (296)
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
doaj +1 more source
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +1 more source
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
openaire +2 more sources
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
doaj +1 more source
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
openaire +1 more source
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
doaj +1 more source
Modelling zero-truncated overdispersed antenatal health care count data of women in Bangladesh.
PLoS ONE, 2020 Overdispersion in count data analysis is very common in many practical fields of health sciences. Ignorance of the presence of overdispersion in such data analysis may cause misleading inferences and thus lead to incorrect interpretations of the results.
Zakir Hossain +3 more
doaj +1 more source
Understanding the impact of correlation within pair‐bonds on Cormack–Jolly–Seber models
Ecology and Evolution, 2021 The Cormack–Jolly–Seber (CJS) model and its extensions have been widely applied to the study of animal survival rates in open populations. The model assumes that individuals within the population of interest have independent fates. It is, however, highly
Alexandru M. Draghici +2 more
doaj +1 more source