Results 11 to 20 of about 46,328 (287)
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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Modelling count data with overdispersion and spatial effects [PDF]
, 2005 In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. We account for unobserved heterogeneity in the data in two ways. On the one hand, we consider more flexible models than a common Poisson model
Czado, Claudia, Gschlößl, Susanne
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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
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IJAIN (International Journal of Advances in Intelligent Informatics), 2016 Poisson distribution is one of discrete distribution that is often used in modeling of rare events. The data obtained in form of counts with non-negative integers. One of analysis that is used in modeling count data is Poisson regression.
Lili Puspita Rahayu +2 more
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Entropy, 2022 Numerous methods have been developed for longitudinal binomial data in the literature. These traditional methods are reasonable for longitudinal binomial data with a negative association between the number of successes and the number of failures over ...
Xiaolei Zhang +3 more
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PENERAPAN REGRESI ZERO-INFLATED NEGATIVE BINOMIAL (ZINB) UNTUK PENDUGAAN KEMATIAN ANAK BALITA
E-Jurnal Matematika, 2013 One method of regression analysis used to analyze the count data is Poisson regression. Poisson regression requires that the mean value equal to the value of variance (equidispersion).
NI MADE SEKARMINI +2 more
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Zero-inflated generalized Poisson models with regression effects on the mean, dispersion and zero-inflation level applied to patent outsourcing rates [PDF]
, 2006 This paper focuses on an extension of zero-inflated generalized Poisson (ZIGP) regression models for count data. We discuss generalized Poisson (GP) models where dispersion is modelled by an additional model parameter.
Czado, Claudia +2 more
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Anthelmintic Treatment and the Stability of Parasite Distribution in Ruminants
Animals, 2023 Parasites are generally overdispersed among their hosts, with far-reaching implications for their population dynamics and control. The factors determining parasite overdispersion have long been debated.
Eric R. Morgan +4 more
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PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON
E-Jurnal Matematika, 2013 Poisson regression was used to analyze the count data which Poisson distributed. Poisson regression analysis requires state equidispersion, in which the mean value of the response variable is equal to the value of the variance.
PUTU SUSAN PRADAWATI +2 more
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