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A New Poisson Generalized Lindley Regression Model
Austrian Journal of Statistics, 2023 In this paper, a new count distribution is introduced. It is a mixture of the Poisson and generalized Lindley distributions. Statistical properties of the proposed distribution including the factorial moments, probability generating function, moment ...
Yupapin Atikankul
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Modelling Generalized Poisson Regression in the Number of Dengue Hemorrhagic Fever (DHF) in East Nusa Tenggara [PDF]
E3S Web of Conferences, 2020 Regression analysis is an analysis used to model the relationship between the dependent variable (Y) and the independent variable (X). If the dependent variable is a discrete random variable, it is developed using the Poisson regression model.
Prahutama Alan +2 more
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Can Generalized Poisson model replace any other count data models? An evaluation
Clinical Epidemiology and Global Health, 2021 Background: Count data represents the number of occurrences of an event within a fixed period of time. In count data modelling, overdispersion is inevitable.
Bijesh Yadav +6 more
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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
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Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease
Entropy, 2021 For count data, though a zero-inflated model can work perfectly well with an excess of zeroes and the generalized Poisson model can tackle over- or under-dispersion, most models cannot simultaneously deal with both zero-inflated or zero-deflated data and
Guoxin Zuo +3 more
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Generalized Poisson sigma models [PDF]
Physics Letters B, 2001 A general master action in terms of superfields is given which generates generalized Poisson sigma models by means of a natural ghost number prescription. The simplest representation is the sigma model considered by Cattaneo and Felder. For Dirac brackets considerably more general models are generated.
Batalin, I., Marnelius, R.
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Barekeng, 2022 Traffic accidents that always increase along with the increasing population growth and the number of vehicles impact the national economy. The number of traffic accidents is a count data that a Poisson distribution can approximate. The Poisson regression
M Al Haris, Prizka Rismawati Arum
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Poisson Flow Generative Models
, 2022 We propose a new "Poisson flow" generative model (PFGM) that maps a uniform distribution on a high-dimensional hemisphere into any data distribution. We interpret the data points as electrical charges on the $z=0$ hyperplane in a space augmented with an additional dimension $z$, generating a high-dimensional electric field (the gradient of the solution
Xu, Yilun +3 more
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Entropy, 2023 A new model of inertial neural networks with a generalized piecewise constant argument as well as unpredictable inputs is proposed. The model is inspired by unpredictable perturbations, which allow to study the distribution of chaotic signals in neural ...
Marat Akhmet +2 more
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MethodsX, 2023 This article constructs a new model based on multivariate adaptive generalized Poisson regression splines (MAGPRS) and geographically weighted generalized Poisson regression (GWGPR), which is known as multivariate adaptive geographically weighted ...
Riry Sriningsih +2 more
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