Results 21 to 30 of about 170,730 (268)
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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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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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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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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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 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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A Random-Effects Log-Linear Model with Poisson Distributions
Revstat Statistical Journal, 2003 In several applications data are grouped and there are within-group correlations. With continuous data, there are several available models that are often used; with counting data, the Poisson distribution is the natural choice. In this paper a mixed log-
Maria Alexandra Seco, António St. Aubyn
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A Flexible Mixed Model for Clustered Count Data
Stats, 2022 Clustered count data are commonly modeled using Poisson regression with random effects to account for the correlation induced by clustering. The Poisson mixed model allows for overdispersion via the nature of the within-cluster correlation, however ...
Darcy Steeg Morris, Kimberly F. Sellers
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Models for Rates with Poisson Errors
Biometrics, 1984 In a recent paper, Frome (1983) described the fitting of models with Poisson errors and data in the form of rates. Some of the models considered are log-linear and hence can be fitted simply by GLIM or by any package that handles log-linear models; some are not and require either special treatment in GLIM or the use of a program that handles iterative ...
J. A. Nelder, E. L. Frome
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On the AKSZ Formulation of the Poisson Sigma Model [PDF]
Letters in Mathematical Physics, 2001 We review and extend the Alexandrov–Kontsevich–Schwarz–Zaboronsky construction of solutions of the Batalin–Vilkovisky classical master equation. In particular, we study the case of sigma models on manifolds with boundary. We show that a special case of this construction yields the Batalin–Vilkovisky action functional of the Poisson sigma model on a ...
Cattaneo Alberto S., Felder Giovanni
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