Results 31 to 40 of about 213,890 (318)
A Poisson model for random multigraphs [PDF]
Bioinformatics, 2010 AbstractMotivation: Biological networks are often modeled by random graphs. A better modeling vehicle is a multigraph where each pair of nodes is connected by a Poisson number of edges. In the current model, the mean number of edges equals the product of two propensities, one for each node.
John M. O. Ranola +4 more
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MODEL EKSPONENSIAL GANDA PADA PROSES STOKASTIK (STUDI KASUS DI STASIUN PURWOSARI)
Media Statistika, 2015 In general, mathematical modeling is divided into two, namely the model of deterministic and stochastic models. On stochastic modeling involves several processes among them are the Poisson process, the process of Bernoulli, Gaussian processes, the ...
Sugito Sugito, Yuciana Wilandari
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Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression [PDF]
, 2005 Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zero-inflation occur.
Min, Aleksey, Czado, Claudia
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Intensity estimation of non-homogeneous Poisson processes from shifted trajectories [PDF]
, 2013 In this paper, we consider the problem of estimating nonparametrically a mean pattern intensity λ from the observation of n independent and non-homogeneous Poisson processes N1,…,Nn on the interval [0,1].
Marteau, Clément +3 more
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Jurnal Diferensial, 2020 terbaik dan faktor-faktor yang mempengaruhi angka kematian ibu akibat melahirkan. Regresi Poisson merupakan salah satu regresi nonlinier yang sering digunakan untuk memodelkan hubungan antara variabel respon yang berupa data diskrit dengan variabel ...
Katarina J.V. Nggonde
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Optimal Poisson Cognitive System with Markov Learning Model
Открытое образование (Москва), 2021 The aim of the study is to develop a mathematical model of the trained Markov cognitive system in the presence of discrete training and interfering random stimuli arising at random times at its input.
A. A. Solodov
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The Poisson Maximum Entropy Model for Homogeneous Poisson Processes
Communications in Statistics - Simulation and Computation, 2016 Our main interest is parameter estimation using maximum entropy methods in the prediction of future events for Homogeneous Poisson Processes when the distribution governing the distribution of the parameters is unknown. We intend to use empirical Bayes techniques and the maximum entropy principle to model the prior information.
Lotfi Khribi +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.
Erhardt, Vinzenz +2 more
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Modeling stand mortality using Poisson mixture models with mixed-effects
iForest - Biogeosciences and Forestry, 2015 Stand mortality models play an important role in simulating stand dynamic processes. Periodic stand mortality data from permanent plots tend to be dispersed, and frequently contain an excess of zero counts. Such data have commonly been analyzed using the
Zhang X-Q, Lei Y-C, Liu X-Z
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The sparse Poisson means model
Electronic Journal of Statistics, 2015 We consider the problem of detecting a sparse Poisson mixture. Our results parallel those for the detection of a sparse normal mixture, pioneered by Ingster (1997) and Donoho and Jin (2004), when the Poisson means are larger than logarithmic in the sample size.
Arias-Castro, Ery, Wang, Meng
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