Relevant bibliographies by topics / Poissom regression

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Poissom regression'

Author: Grafiati
Published: 8 September 2021
Last updated: 29 July 2025

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Journal articles on the topic "Poissom regression"

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Sormin, Corry, Gusmanely Z, and Nurhidayah Nurhidayah. "Generalized Poisson Regression Type-II at Jambi City Health Office." Eksakta : Berkala Ilmiah Bidang MIPA 21, no. 1 (2020): 54–58. http://dx.doi.org/10.24036/eksakta/vol21-iss1/222.

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One statistical analysis is regression analysis. One regression that has the assumption of poisson distribution is poisson regression which has the assumption of poisson distribution. Neonatal deaths are still very rare, so the proper analysis is used, namely Generalized Poisson Regression. This regression method is specifically used for Poissson distributed data. The stages that will be carried out in this research are Poisson distribution test and equidispersion assumption, parameter estimation, model feasibility test and best model selection. Data from the Jambi City Health Office in 2018 s
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Aickin, Mikel. "Poisson Regression." American Statistician 39, no. 2 (1985): 145. http://dx.doi.org/10.2307/2682825.

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Warner, Pamela. "Poisson regression:." Journal of Family Planning and Reproductive Health Care 41, no. 3 (2015): 223–24. http://dx.doi.org/10.1136/jfprhc-2015-101262.

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Bangdiwala, Shrikant I. "Regression: Poisson." International Journal of Injury Control and Safety Promotion 25, no. 4 (2018): 465–66. http://dx.doi.org/10.1080/17457300.2018.1526365.

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Yang, Shengping, and Gilbert Berdine. "Poisson Regression." Southwest Respiratory and Critical Care Chronicles 3, no. 9 (2015): 61. http://dx.doi.org/10.12746/swrccc.v3i9.191.

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Sedgwick, P. "Poisson regression." BMJ 349, oct10 2 (2014): g6150. http://dx.doi.org/10.1136/bmj.g6150.

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Koletsi, Despina, and Nikolaos Pandis. "Poisson regression." American Journal of Orthodontics and Dentofacial Orthopedics 152, no. 2 (2017): 284–85. http://dx.doi.org/10.1016/j.ajodo.2017.05.009.

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Jeong, Kwang Mo. "A Study on Tests for Zero-Inflated Poisson Regression." Korean Data Analysis Society 21, no. 6 (2019): 2737–49. http://dx.doi.org/10.37727/jkdas.2019.21.6.2737.

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Hayat, Matthew J., and Melinda Higgins. "Understanding Poisson Regression." Journal of Nursing Education 53, no. 4 (2014): 207–15. http://dx.doi.org/10.3928/01484834-20140325-04.

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Tsou, Tsung-Shan. "Robust Poisson regression." Journal of Statistical Planning and Inference 136, no. 9 (2006): 3173–86. http://dx.doi.org/10.1016/j.jspi.2004.12.008.

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Dissertations / Theses on the topic "Poissom regression"

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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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Nilsson, Philip, and Sebastian Nilsson. "Application of Poisson Regression on Traffic Safety." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-168201.

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This study presents a model that explains the traffic fatality by exploring the Poisson regression model using two types of explanatory variables – referred to as internal and external factors. Internal factors contain variables closely linked to traffic safety, such as speed limits and belt usage (Strandroth et al., 2012), whereas external factors comprise a set of variables that the Swedish Transport Administration cannot control, such as the economy and demographic change (Wiklund et al., 2012). The purpose of the study is to evaluate the impact that internal and external factors have on th
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Ludvigsen, Jesper, and Adam Grünwald. "Predicting the NHL playoffs with Poisson regression." Thesis, Uppsala universitet, Statistiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-323435.

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Using historical data from the past two seasons of the National Hockey League, three different prediction models based on Poisson regression are developed. The aim is to determine whether taking into account the recent form of a team as well as data from how they have previously performed against their opponent can help make better predictions of how many goals they will score against this opponent and thereby calculate the likelihood of each outcome. The three models are evaluated using different measures, for example comparing the odds yielded by the models against the odds of bookmakers. Di
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White, Lisa A. "Predicting hospital admissions with Poisson regression analysis." Thesis, Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Jun/09Jun%5FWhite.pdf.

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2009.<br>Thesis Advisor(s): Whitaker, Lyn R. "June 2009." Description based on title screen as viewed on July 14, 2009. Author(s) subject terms: Poisson regression, MTF, military treatment facility, hospital admissions. Includes bibliographical references (p. 53-54). Also available in print.
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Roemmele, Eric S. "A Flexible Zero-Inflated Poisson Regression Model." UKnowledge, 2019. https://uknowledge.uky.edu/statistics_etds/38.

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A practical problem often encountered with observed count data is the presence of excess zeros. Zero-inflation in count data can easily be handled by zero-inflated models, which is a two-component mixture of a point mass at zero and a discrete distribution for the count data. In the presence of predictors, zero-inflated Poisson (ZIP) regression models are, perhaps, the most commonly used. However, the fully parametric ZIP regression model could sometimes be restrictive, especially with respect to the mixing proportions. Taking inspiration from some of the recent literature on semiparametric mi
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Khoury, Bassel. "A poisson regression model for assessing force majeure claims." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103839.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 103-104).<br>Empirical legal analysis is an emerging discipline of statistical and legal scholarship. Despite its importance, however, there is a lack of empirical research on the affirmative defense of force majeure, which eliminates liability for a breach of contract in the case of an unforeseeable and uncontrollable event that renders performance impossible. This study seeks to fill the gap in the
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Zaldivar, Cynthia. "On the Performance of some Poisson Ridge Regression Estimators." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3669.

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Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produc
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Mendes, Clarice Camargo. "Modelos para dados de contagem com aplicações." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307184.

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Orientador: Hildete Prisco Pinheiro<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica<br>Made available in DSpace on 2018-08-08T17:00:10Z (GMT). No. of bitstreams: 1 Mendes_ClariceCamargo_M.pdf: 1127292 bytes, checksum: f015352011300a41bb50c17c81a49bb1 (MD5) Previous issue date: 2007<br>Resumo: Ao lidarmos com dados de contagem, uma abordagem possível é estimar um Modelo Linear Generalizado com distribuição de Poisson. Freqüentemente nestes modelos costuma surgir o problema da superdispersão, um fenômeno que aparece q
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Lora, Mayra Ivanoff. "Modelos de regressão beta-binomial/poisson para contagens bivariadas." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-09062011-095707/.

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Propomos um modelo Beta-Binomial/Poisson para dados provenientes de um estudo com doentes de Parkinson, que consistiu em contar durante um minuto quantas tarefas foram realizadas e destas, quantas de maneira correta, antes e depois de um treinamento. O objetivo era verificar se o treinamento aumentava o número de tentativas e a porcentagem de acerto, o que destaca o aspecto bivariado do problema. Esse modelo considera tal aspecto, usa uma distribuição mais adequada a dados de contagem e ainda suporta a sobredispersão presente nos dados. Obtemos estimadores de máxima verossimilhança dos parâmet
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Lora, Mayra Ivanoff. "Modelos Beta-Binomial/Poisson-Gama para contagens bivariadas repetidas." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-27082009-120419/.

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Em Lora e Singer (Statistics in Medicine, 2008), propusemos um modelo Beta- Binomial/Poisson p-variado para análise dos dados provenientes de um estudo que consistiu em contar o número de tentativas e acertos de um exercício manual com duração de um minuto realizado por doentes de Parkinson, antes e depois de um treinamento. O objetivo era verificar se o treinamento aumentava o número de tentativas e a porcentagem de acerto, o que destaca o aspecto bivariado do problema. Esse modelo leva tais características em consideração, usa uma distribuição adequada para dados de contagem e ainda acomoda
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Books on the topic "Poissom regression"

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Abdolell, Mohamed. Poisson regression trees. National Library of Canada, 1995.

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Abdolell, Mohamed. Poisson regression trees. Universiy of Toronto, Dept. of Statistics, 1994.

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Li, Joseph T. C. A poisson regression analysis of the academic setback in Naval Training deadtime. Naval Postgraduate School, 2000.

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Shi, Feng. Learn About Poisson Regression in R With Data From the Global Health Observatory (2015). SAGE Publications Ltd., 2019. http://dx.doi.org/10.4135/9781526473486.

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Gaver, Donald Paul. Regression analysis of hierarchical Poisson-like event rate data: Superpopulation model effect on predictions. Naval Postgraduate School, 1990.

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Lasse, Fridstrøm, and Nordic Council of Ministers, eds. Explaining the variation in road accident counts: A four-country, generalized Poisson regression analysis. Nordic Council of Ministers, 1993.

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Reid, Abigail-Kate, and Nick Allum. Learn About Poisson Regression in Stata With Data From the Behavioral Risk Factor Surveillance System (2013). SAGE Publications, Ltd., 2020. http://dx.doi.org/10.4135/9781529711387.

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Violent Crime and Poisson Regression. GRIN Verlag GmbH, 2013.

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Negative Binomial Regression. Cambridfe University Press, 2007.

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Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2008.

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Book chapters on the topic "Poissom regression"

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Poisson Regression." In Statistics Applied to Clinical Studies. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2863-9_23.

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Stanberry, Larissa. "Poisson Regression." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1199.

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Musa, Kamarul Imran, Wan Nor Arifin Wan Mansor, and Tengku Muhammad Hanis. "Poisson Regression." In Data Analysis in Medicine and Health using R. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003296775-10.

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Tutz, Gerhard. "Poisson Regression." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_450.

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Dugard, Pat, John Todman, and Harry Staines. "Poisson regression." In Approaching Multivariate Analysis, 2nd ed. Routledge, 2022. http://dx.doi.org/10.4324/9781003343097-13.

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Broström, Göran. "Poisson Regression." In Event History Analysis with R, 2nd ed. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429503764-5.

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Tutz, Gerhard. "Poisson Regression." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-69359-9_475.

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Winkelmann, Rainer, and Klaus F. Zimmermann. "Robust Poisson Regression." In Advances in GLIM and Statistical Modelling. Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2952-0_31.

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Cummings, Peter. "Exact Poisson Regression." In Analysis of Incidence Rates. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429055713-23.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "More on Poisson Regressions." In Regression Analysis in Medical Research. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71937-5_14.

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Conference papers on the topic "Poissom regression"

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Kalavakunta, Sumanth, and V. Parthipan. "Comparative Analysis of Accuracy For Predicting Earthquake Occurrence Using Linear Regression Over Poisson Regression." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877622.

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Rizal, Ahmad Syaiful, Purhadi, and Dedy Dwi Prastyo. "Bivariate Poisson Inverse Gamma INAR(1) Regression Model: Healthcare Service Visits by Health Insurance Members Case Study." In 2024 9th International Conference on Business and Industrial Research (ICBIR). IEEE, 2024. https://doi.org/10.1109/icbir61386.2024.10875799.

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Okuno, Alex, and Alberto Ferreira. "Generalized linear tree: a flexible algorithm for predicting continuous variables." In LatinX in AI at International Conference on Machine Learning 2021. Journal of LatinX in AI Research, 2021. http://dx.doi.org/10.52591/lxai2021072420.

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Tree-based models are popular among regression methods to predict continuous variables. Also, Generalized Linear Models (GLMs) are pretty standard in many statistical applications and provide a generalization to many of the most commonly applied statistical procedures. However, in most regression tree methods, there is only one theoretical model associated for prediction in the final nodes, like multiple linear regression, logistic regressions, polynomial models, Poisson models, among others. We, therefore, propose a new tree method in which we estimate a GLM in each leaf node of the estimated
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Darnah. "Modelling of filariasis in East Java with Poisson regression and generalized Poisson regression models." In SYMPOSIUM ON BIOMATHEMATICS (SYMOMATH 2015). AIP Publishing LLC, 2016. http://dx.doi.org/10.1063/1.4945064.

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Yasmirullah, Septia Devi Prihastuti, Bambang Widjanarko Otok, Jerry Dwi Trijoyo Purnomo, and Dedy Dwi Prastyo. "Comparison of multivariate adaptive Poisson Regression spline and multivariate adaptive generalized Poisson Regression spline." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGY AND MULTIDISCIPLINE (ICATAM) 2021: “Advanced Technology and Multidisciplinary Prospective Towards Bright Future” Faculty of Advanced Technology and Multidiscipline. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0119385.

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Saputro, Dewi Retno Sari, Ade Susanti, and Nafisa Berliana Indah Pratiwi. "The handling of overdispersion on Poisson regression model with the generalized Poisson regression model." In THE THIRD INTERNATIONAL CONFERENCE ON MATHEMATICS: Education, Theory and Application. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0040330.

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Sriningsih, Riry, Bambang Widjanarko Otok, and Sutikno. "Modified multivariate adaptive regression spline and generalized Poisson regression." In PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE OF MATHEMATICS AND MATHEMATICS EDUCATION, 2022: Innovative Research of Mathematics and Mathematics Education to Face the 4th Industrial Revolution Challenges. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0204453.

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Zamani, Hossein, and Noriszura Ismail. "Score test for testing Poisson regression against generalized Poisson alternatives." In PROCEEDINGS OF THE 20TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Research in Mathematical Sciences: A Catalyst for Creativity and Innovation. AIP, 2013. http://dx.doi.org/10.1063/1.4801268.

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Chan, Antoni B., and Nuno Vasconcelos. "Bayesian Poisson regression for crowd counting." In 2009 IEEE 12th International Conference on Computer Vision (ICCV). IEEE, 2009. http://dx.doi.org/10.1109/iccv.2009.5459191.

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Llosa, Carlos, and Daniel Dunlavy. "Poisson-response Tensor-on-Tensor Regression." In Conference on Data Analysis 2023 - Santa Fe, New Mexico, United States of America - March - 2023. US DOE, 2023. http://dx.doi.org/10.2172/2432049.

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Reports on the topic "Poissom regression"

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Chung, C. F. A Fortran 77 Program For Poisson Regression. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1988. http://dx.doi.org/10.4095/130709.

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Di Gessa, Giorgio, Paola Zaninotto, and Andrea Lisette Castro. Applied Regression with Continuous and Categorical Data. Instats Inc., 2024. http://dx.doi.org/10.61700/7xri7v6fq6k8o1543.

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This comprehensive 4-day workshop equips researchers with advanced skills in both linear and Poisson regression analysis using real-world data. Offered by professors Zaninotto and Di Gessa from the Institute of Epidemiology &amp; Health Care at UCL, participants will enhance their data preparation, model building, and interpretation capabilities, gaining practical, hands-on experience essential for impactful research across various social, health, and life science disciplines.
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Frome E.L., Watkins J. P. ,. Ellis E. D. Poisson Regression Analysis of Illness and Injury Surveillance Data. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1060522.

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Moral, Rafael. Introduction to Generalized Linear Models. Instats Inc., 2024. http://dx.doi.org/10.61700/vteee3zjf6fsm1478.

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This seminar provides a comprehensive introduction to Generalized Linear Models (GLMs), covering binary, binomial, categorical logistic regression, Poisson regression, and advanced topics like overdispersion and zero-inflated models. Participants will gain theoretical knowledge and practical skills in applying GLMs using R, enhancing their ability to perform rigorous statistical analyses in various research scenarios.
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Sánchez-Páez, David A. Effects of income inequality on COVID-19 infections and deaths during the first wave of the pandemic: Evidence from European countries. Verlag der Österreichischen Akademie der Wissenschaften, 2021. http://dx.doi.org/10.1553/populationyearbook2022.res1.1.

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Evidence from research on infectious diseases suggests that income inequality is related to higher rates of infection and death in disadvantaged population groups. Our objective is to examine whether there was an association between income inequality and the numbers of cases and deaths during the first wave of the COVID- 19 pandemic in European countries. We determined the duration of the first wave by first smoothing the number of daily cases, and then using a LOESS regression to fit the smoothed trend. Next, we estimated quasi-Poisson regressions. Results from the bivariate models suggest th
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Liu, Zhiyuan, Tze-San Lee, and T. J. Kotek. Poisson regression analysis of mortality among male workers at a thorium-processing plant. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/10148890.

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Gaver, Donald P., Patricia A. Jacobs, and I. G. O'Muircheartaigh. Regression Analysis of Hierarchical Poisson-Like Event Rate Data: Super- Population Model Effect on Predictions. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada230297.

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Navarro, Adoracion. Subnational Infrastructure Development and Internal Migration in the Philippines. Philippine Institute for Development Studies, 2023. http://dx.doi.org/10.62986/dp2023.20.

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Making a comprehensive comparison of subnational levels of infrastructure development in the Philippines is difficult due to the uneven availability of data on infrastructure indicators across geo-political areas. This study shows this is possible at the regional level by developing a demonstration composite subnational infrastructure development index. The study constructed a regional infrastructure development index by picking indicators based on representativeness in the infrastructure subsectors and the uniform availability of data across regions. It also presents one useful application of
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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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Pintar, Adam L., Emil Simiu, Franklin T. Lombardo, and Marc L. Levitan. Simple Guide for Evaluating and Expressing the Uncertainty of NIST MeasuremenMaps of Non-hurricane Non-tornadic Wind Speeds With Specified Mean Recurrence Intervals for the Contiguous United States Using a Two-Dimensional Poisson Process Extreme Value Model and Local Regressiont Results. National Institute of Standards and Technology, 2015. http://dx.doi.org/10.6028/nist.sp.500-301.

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