Bibliografías temáticas / Poisson distribution

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Literatura académica sobre el tema "Poisson distribution"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Poisson distribution"

1

Loukas, Sotirios, and H. Papageorgiou. "On a trivariate Poisson distribution." Applications of Mathematics 36, no. 6 (1991): 432–39. http://dx.doi.org/10.21136/am.1991.104480.

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Nganga, P. C. Batsindila, R. F. Mizelé Kitoti, E. Nguessolta, and D. Mizère. "A NOTE ON THE BIVARIATE GENERALIZED POISSON DISTRIBUTION OF TYPE 1." Far East Journal of Theoretical Statistics 69, no. 2 (2025): 155–68. https://doi.org/10.17654/0972086325007.

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Given the univariate generalized Poisson distribution as defined by Déniz and Sarabia [5], in this paper, we construct a bivariate generalized Poisson distribution of type 1 whose marginal distributions are univariate generalized Poisson distributions according to Déniz and Sarabia [5]. We also show that this distribution belongs to the family of bivariate Poisson distributions. Under certain conditions, this distribution converges in distribution to the bivariate Poisson distribution of Berkhout and Plug [4]. It also converges to the bivariate Poisson distribution of Lakshminarayana et al. [9
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Bidounga, R., P. C. Batsindila Nganga, L. Niéré, and D. Mizère. "A Note on the (Weighted) Bivariate Poisson Distribution." European Journal of Pure and Applied Mathematics 14, no. 1 (2021): 192–203. http://dx.doi.org/10.29020/nybg.ejpam.v14i1.3895.

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In the recent statistical literature, the univariate Poisson distribution has been generalized by many authors, among them: the univariate weighted Poisson distribution [13], the generalized univariate Poisson distribution [7], the bivariate Poisson distribution according to Holgate [11], the bivariate Poisson distribution according to Lakshminarayana, Pandit and Srinivasa Rao [15], the bivariate Poisson distribution according to Berkhout and Plug [4], the bivariate weighted Poisson distribution according to Elion et al. [8] and the generalized bivariate Poisson distribution according to Famoy
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SHANKER, Rama. "The Discrete Poisson-Aradhana Distribution." Turkiye Klinikleri Journal of Biostatistics 9, no. 1 (2017): 12–22. http://dx.doi.org/10.5336/biostatic.2017-54834.

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V. R., Saji Kumar. "α - Poisson Distribution". Calcutta Statistical Association Bulletin 54, № 3-4 (2003): 275–80. http://dx.doi.org/10.1177/0008068320030312.

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Shanker, Rama, and Kamlesh Kumar Shukla. "The Poisson-Adya distribution." Biometrics & Biostatistics International Journal 11, no. 3 (2022): 100–103. http://dx.doi.org/10.15406/bbij.2022.11.00361.

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In this paper a Poisson mixture of Adya distribution called Poisson-Adya distribution has been suggested. The expressions of statistical constants including coefficients of variation, skewness, kurtosis and index of dispersion have been obtained and their behavior for varying values of parameter has been studied. It is observed that the obtained distribution is unimodal, has increasing hazard rate and over-dispersed. Maximum likelihood estimation and method of moment have been discussed for estimating parameter. Finally, the goodness of fit of the proposed distribution and its comparison with
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Gao, Mingchu. "Compound bi-free Poisson distributions." Infinite Dimensional Analysis, Quantum Probability and Related Topics 22, no. 02 (2019): 1950014. http://dx.doi.org/10.1142/s0219025719500140.

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In this paper, we study compound bi-free Poisson distributions for two-faced families of random variables. We prove a Poisson limit theorem for compound bi-free Poisson distributions. Furthermore, a bi-free infinitely divisible distribution for a two-faced family of self-adjoint random variables can be realized as the limit of a sequence of compound bi-free Poisson distributions of two-faced families of self-adjoint random variables. If a compound bi-free Poisson distribution is determined by a positive number and the distribution of a two-faced family of finitely many random variables, which
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Bamigbala, Olateju Alao, Saidu S. Abdulkadir, Adesupo A. Akinrefon, and Jibasen Danjuma. "Poisson Sauleh Distribution and its Properties." International Journal of Development Mathematics (IJDM) 2, no. 2 (2025): 246–66. https://doi.org/10.62054/ijdm/0202.14.

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This study introduces the Poisson-Sauleh distribution (PSuD), a novel statistical model designed to effectively handle overdispersed and heavy-tailed count data. Traditional models, such as the Poisson and Negative Binomial distributions, often fall short in accurately modeling real-world data characterized by greater variability than the mean and heavy-tailed count data. The PSuD is a mixture of the Poisson and Sauleh distributions, while Sauleh distribution is also a mixture of Exponential and Gamma distributions, to enhance flexibility and fit for complex datasets. We derive the PSuD and ex
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9

Shanker, Rama, and Kamlesh Kumar Shukla. "A new three-parameter size-biased poisson-lindley distribution with properties and applications." Biometrics & Biostatistics International Journal 9, no. 1 (2020): 1–4. http://dx.doi.org/10.15406/bbij.2020.09.00294.

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A new three-parameter size-biased Poisson-Lindley distribution which includes several one parameter and two-parameter size-biased distributions including size-biased geometric distribution (SBGD), size-biased negative binomial distribution (SBNBD), size-biased Poisson-Lindley distribution (SBPLD), size-biased Poisson-Shanker distribution (SBPSD), size-biased two-parameter Poisson-Lindley distribution-1 (SBTPPLD-1), size-biased two-parameter Poisson-Lindley distribution-2(SBTPPLD-2), size-biased quasi Poisson-Lindley distribution (SBQPLD) and size-biased new quasi Poisson-Lindley distribution (
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Deshmukh, S. R., and M. S. Kasture. "BIVARIATE DISTRIBUTION WITH TRUNCATED POISSON MARGINAL DISTRIBUTIONS." Communications in Statistics - Theory and Methods 31, no. 4 (2002): 527–34. http://dx.doi.org/10.1081/sta-120003132.

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Tesis sobre el tema "Poisson distribution"

1

Gu, Kangxia. "Testing the rates of Poisson distribution." Ann Arbor, Mich. : ProQuest, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3213456.

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Thesis (Ph.D. in Statistical Science)--S.M.U.<br>Title from PDF title page (viewed July 6, 2007). Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1504. Advisers: Hon Keung Tony Ng; William R. Schucany. Includes bibliographical references.
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2

Wang, Ling. "Homogeneity tests for several poisson populations." HKBU Institutional Repository, 2008. http://repository.hkbu.edu.hk/etd_ra/909.

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SILVA, PRISCILLA FERREIRA DA. "A BIVARIATE GARMA MODEL WITH CONDITIONAL POISSON DISTRIBUTION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2013. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=22899@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>Os modelos lineares generalizados auto regressivos com médias móveis (do inglês GARMA), possibilitam a modelagem de séries temporais de dados de contagem com estrutura de correlação similares aos dos modelos ARMA. Neste trabalho é desenvolvida uma extensão multivariada do modelo GARMA, considerando a especificação de um modelo Poisson bivariado a partir da distribuição de Kocherlakota e Kocherlakota (1992), a qual será
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Wan, Wai-yin. "Analysis of Poisson count data using Geometric Process model." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37836493.

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Wan, Wai-yin, and 溫慧妍. "Analysis of Poisson count data using Geometric Process model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37836493.

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Buchmann, Boris. "Decompounding an estimation problem for the compound poisson distribution /." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=962736910.

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van, de Ven Remy Julius. "Estimation in mixed Poisson regression models." Thesis, The University of Sydney, 1996. https://hdl.handle.net/2123/26822.

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This thesis considers estimation of the parameters associated with models for count data displaying over-dispersion relative to the Poisson distribution where the over-dispersion is modelled using mixing. It is divided into seven chapters with Chapters Two to Five specific to the over-dispersed Poisson problem whilst Chapter Seven, which uses results from Chapter Six, is more general. The motivation for some of this work was the modelling of repeat counts of the number of fibres contained on microscopic slides as obtained by asbestos fibre counters and the subsequent estimation of mean fibre c
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8

Pfister, Mark. "Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etd/3459.

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A probability distribution is a statistical function that describes the probability of possible outcomes in an experiment or occurrence. There are many different probability distributions that give the probability of an event happening, given some sample size n. An important question in statistics is to determine the distribution of the sum of independent random variables when the sample size n is fixed. For example, it is known that the sum of n independent Bernoulli random variables with success probability p is a Binomial distribution with parameters n and p: However, this is not true when
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Rodrigues, Cristiane. "Distribuições em série de potências modificadas inflacionadas e distribuição Weibull binominal negativa." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-28062011-095106/.

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Neste trabalho, alguns resultados, tais como, função geradora de momentos, relações de recorrência para os momentos e alguns teoremas da classe de distribuições em séries de potencias modificadas (MPSD) proposta por Gupta (1974) e da classe de distribuições em séries de potências modificadas inflacionadas (IMPSD) tanto em um ponto diferente de zero como no ponto zero são apresentados. Uma aplicação do Modelo Poisson padrão, do modelo binomial negativo padrão e dos modelos inflacionados de zeros para dados de contagem, ZIP e ZINB, utilizando-se as técnicas dos MLGs, foi realizada para dois conj
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Gagnon, Karine. "Distribution et abondance des larves d'éperlan arc-en-ciel (Osmerus mordax) au lac Saint-Jean /." Thèse, Chicoutimi : Université du Québec à Chicoutimi, 2005. http://theses.uqac.ca.

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Libros sobre el tema "Poisson distribution"

1

Barbour, A. D. Poisson approximation. Clarendon Press, 1992.

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Grandell, Jan. Mixed Poisson processes. Chapman & Hall, 1997.

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Lindsay, Glenn F. Recruiter productivity and the Poisson distribution. Naval Postgraduate School, 1994.

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Feng, Shui. The Poisson-Dirichlet Distribution and Related Topics. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11194-5.

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T, Schreuder Hans, Terrazas Gerardo H, and Rocky Mountain Research Station (Fort Collins, Colo.), eds. Poisson sampling: The adjusted and unadjusted estimator revisited. U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, 1998.

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Harris, Ian Richard. Smooth and predictive estimates for the compound Poisson distribution. University of Birmingham, 1987.

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Marijtje A. J. van Duijn. Mixed models for repeated count data. DSWO Press, Leiden University, 1993.

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A, Kutoyants Yu. Statistical inference for spatial Poisson processes. Springer, 1998.

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Heldt, John J. Quality sampling and reliability: New uses for the poisson distribution. St. Lucie Press, 1999.

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Streit, Roy L. Poisson Point Processes: Imaging, Tracking, and Sensing. Springer Science+Business Media, LLC, 2010.

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Capítulos de libros sobre el tema "Poisson distribution"

1

Gooch, Jan W. "Poisson Distribution." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15324.

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Gooch, Jan W. "Poisson Distribution." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_8909.

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Weik, Martin H. "Poisson distribution." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_14247.

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Čekanavičius, V., and S. Y. Novak. "Markov Binomial distribution." In Compound Poisson Approximation. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003478164-9.

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Gooch, Jan W. "Poisson Ratio Distribution." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_8911.

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Nguyen, Hung T., and Gerald S. Rogers. "The Poisson Distribution." In Springer Texts in Statistics. Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-1013-9_20.

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Jolicoeur, Pierre. "The Poisson distribution." In Introduction to Biometry. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4777-8_19.

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Cummings, Peter. "The Poisson Distribution." In Analysis of Incidence Rates. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429055713-4.

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Russell, Kenneth G. "The Poisson Distribution." In Design of Experiments for Generalized Linear Models. Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9780429057489-5.

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Grandell, Jan. "The mixed Poisson distribution." In Mixed Poisson Processes. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-3117-7_2.

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Actas de conferencias sobre el tema "Poisson distribution"

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Huang, Dihong. "A Sampling Method of Sequential Tests with Sample Size Limit Under Poisson Distribution." In 2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE). IEEE, 2025. https://doi.org/10.1109/eespe63401.2025.10987180.

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Xin, Yuanxue, Lin Ma, Jingyao Wang, et al. "Deployment Optimization of Multi-Cell Multi-User System with Hard Core Poisson Point Distribution." In 2024 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE, 2024. http://dx.doi.org/10.1109/icccworkshops62562.2024.10693817.

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Chen, Xingyu, and Junying Chen. "PDDM: Poisson-Distribution Diffusion Model with Multi-Step Weighted Fusion for Medical Image Segmentation." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650166.

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Abdi, Hashem, Masoumeh Shiri, and Behrooz Shahrokhzadeh. "Proposing a Reliable and Fault-Tolerant Routing Algorithm for IoT Sensor Networks Using Poisson Distribution." In 2024 11th International Symposium on Telecommunications (IST). IEEE, 2024. https://doi.org/10.1109/ist64061.2024.10843568.

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Hubert, Paulo C., Marcelo S. Lauretto, Julio M. Stern, Paul M. Goggans, and Chun-Yong Chan. "FBST for Generalized Poisson Distribution." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: The 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2009. http://dx.doi.org/10.1063/1.3275617.

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SEETHA MAHALAXMI, D., and P. R. K. MURTI. "TAMPER RESISTANCE VIA POISSON DISTRIBUTION." In Proceedings of the 3rd Asian Applied Computing Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2007. http://dx.doi.org/10.1142/9781860948534_0019.

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Adzkiah, A., D. Lestari, and L. Safitri. "Exponential Conway Maxwell Poisson distribution." In PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0059254.

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Fitria, Dina, Nonong Amalita, and Syafriandi. "Poisson Distribution with Discrete Parameter." In Proceedings of the 2nd International Conference on Mathematics and Mathematics Education 2018 (ICM2E 2018). Atlantis Press, 2018. http://dx.doi.org/10.2991/icm2e-18.2018.11.

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Özel, Gamze, and Selen Çakmakyapan. "A new generalized Poisson Lindley distribution." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2016). Author(s), 2017. http://dx.doi.org/10.1063/1.4992404.

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Švihlík, Jan, Zuzana Krbcová, Jaromir Kukal, and Karel Fliegel. "Smoothing of astronomical images with Poisson distribution." In Applications of Digital Image Processing XL, edited by Andrew G. Tescher. SPIE, 2017. http://dx.doi.org/10.1117/12.2274121.

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Informes sobre el tema "Poisson distribution"

1

Lindsay, Glenn F. Recruiter Productivity and the Poisson Distribution. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada286230.

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Bryant, J. L., and A. S. Paulson. Estimation of the Parameters of a Modified Compound Poisson Distribution. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada178540.

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DeLacy, Brendan G., and Janon F. Embury. Infrared Extinction Coefficients of Aerosolized Conductive Flake Powders and Flake Suspensions having a Zero-Truncated Poisson Size Distribution. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada570956.

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Zacks, S., and Gang Li. The Distribution of the Size and Number of Shadows Cast on a Line Segment in a Poisson Random Field. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada233697.

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Vecherin, Sergey, Stephen Ketcham, Aaron Meyer, Kyle Dunn, Jacob Desmond, and Michael Parker. Short-range near-surface seismic ensemble predictions and uncertainty quantification for layered medium. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45300.

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To make a prediction for seismic signal propagation, one needs to specify physical properties and subsurface ground structure of the site. This information is frequently unknown or estimated with significant uncertainty. This paper describes a methodology for probabilistic seismic ensemble prediction for vertically stratified soils and short ranges with no in situ site characterization. Instead of specifying viscoelastic site properties, the methodology operates with probability distribution functions of these properties taking into account analytical and empirical relationships among viscoela
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Guilfoyle, Michael, Ruth Beck, Bill Williams, et al. Birds of the Craney Island Dredged Material Management Area, Portsmouth, Virginia, 2008-2020. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45604.

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This report presents the results of a long-term trend analyses of seasonal bird community data from a monitoring effort conducted on the Craney Island Dredged Material Management Area (CIDMMA) from 2008 to 2020, Portsmouth, VA. The USACE Richmond District collaborated with the College of William and Mary and the Coastal Virginia Wildlife Observatory, Waterbird Team, to conduct year-round semimonthly area counts of the CIDMMA to examine species presence and population changes overtime. This effort provides information on the importance of the area to numerous bird species and bird species’ grou
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Tummala, Rohan, Andrew de Jesus, Natasha Tillett, Jeffrey Nelson, and Christine Lamey. Clinical and Socioeconomic Predictors of Palliative Care Utilization. University of Tennessee Health Science Center, 2021. http://dx.doi.org/10.21007/com.lsp.2020.0006.

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INTRODUCTION: Palliative care continues to gain recognition among primary care providers, as patients suffering from chronic conditions may benefit from use of this growing service. OBJECTIVES: This single-institution quality improvement study investigates the clinical characteristics and socioeconomic status (SES) of palliative care patients and identifies predictors of palliative care utilization. METHODS: Retrospective chart review was used to compare clinical and SES parameters for three groups of patients: (1) palliative care patients who attended at least one visit since the inception of
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