Relevant bibliographies by topics / Bayesian rules

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  2. Dissertations / Theses
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  4. Book chapters
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Academic literature on the topic 'Bayesian rules'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Bayesian rules"

1

Howson, Colin. "Bayesian rules of updating." Erkenntnis 45, no. 2-3 (1996): 195–208. http://dx.doi.org/10.1007/bf00276790.

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Nicholl, Jon, and Steve Goodacre. "Bayesian stopping rules for trials." Lancet 359, no. 9300 (2002): 76. http://dx.doi.org/10.1016/s0140-6736(02)07292-6.

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Parmar, Mahesh KB, David J. Spiegelhalter, Gareth O. Griffiths, Douglas G. Altman, and Robert L. Souhami. "Bayesian stopping rules for trials." Lancet 359, no. 9300 (2002): 76–77. http://dx.doi.org/10.1016/s0140-6736(02)07293-8.

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Kulvichit, Kittisak. "Bayesian stopping rules for trials." Lancet 359, no. 9300 (2002): 77. http://dx.doi.org/10.1016/s0140-6736(02)07294-x.

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Dimitrakakis, Christos, Yang Liu, David C. Parkes, and Goran Radanovic. "Bayesian Fairness." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 509–16. http://dx.doi.org/10.1609/aaai.v33i01.3301509.

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We consider the problem of how decision making can be fair when the underlying probabilistic model of the world is not known with certainty. We argue that recent notions of fairness in machine learning need to explicitly incorporate parameter uncertainty, hence we introduce the notion of Bayesian fairness as a suitable candidate for fair decision rules. Using balance, a definition of fairness introduced in (Kleinberg, Mullainathan, and Raghavan 2016), we show how a Bayesian perspective can lead to well-performing and fair decision rules even under high uncertainty.
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Long, Yuqi, and Xingzhong Xu. "Bayesian decision rules to classification problems." Australian & New Zealand Journal of Statistics 63, no. 2 (2021): 394–415. http://dx.doi.org/10.1111/anzs.12325.

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Majumdar, Dipjyoti, and Arunava Sen. "Ordinally Bayesian Incentive Compatible Voting Rules." Econometrica 72, no. 2 (2004): 523–40. http://dx.doi.org/10.1111/j.1468-0262.2004.00499.x.

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Ankirchner, Stefan, and Maike Klein. "Bayesian sequential testing with expectation constraints." ESAIM: Control, Optimisation and Calculus of Variations 26 (2020): 51. http://dx.doi.org/10.1051/cocv/2019045.

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We study a stopping problem arising from a sequential testing of two simple hypotheses H0 and H1 on the drift rate of a Brownian motion. We impose an expectation constraint on the stopping rules allowed and show that an optimal stopping rule satisfying the constraint can be found among the rules of the following type: stop if the posterior probability for H1 attains a given lower or upper barrier; or stop if the posterior probability comes back to a fixed intermediate point after a sufficiently large excursion. Stopping at the intermediate point means that the testing is abandoned without acce
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Gubler, Philipp, and Makoto Oka. "QCD sum rules in a Bayesian approach." Journal of Physics: Conference Series 312, no. 3 (2011): 032008. http://dx.doi.org/10.1088/1742-6596/312/3/032008.

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van Enk, Steven J. "Bayesian Measures of Confirmation from Scoring Rules." Philosophy of Science 81, no. 1 (2014): 101–13. http://dx.doi.org/10.1086/674205.

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Dissertations / Theses on the topic "Bayesian rules"

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Dellaportas, Petros. "Imbedded integration rules and their applications in Bayesian analysis." Thesis, University of Plymouth, 1990. http://hdl.handle.net/10026.1/2067.

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This thesis deals with the development and application of numerical integration techniques for use in Bayesian Statistics. In particular, it describes how imbedded sequences of positive interpolatory integration rules (PIIR's) obtained from Gauss-Hermite product rules can extend the applicability and efficiency of currently available numerical methods. The numerical strategy suggested by Naylor and Smith (1982) is reviewed, criticised and applied to some examples with real and artificial data. The performance of this strategy is assessed from the viewpoint of 3 criteria: reliability, efficienc
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Huszár, Ferenc. "Scoring rules, divergences and information in Bayesian machine learning." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648333.

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Nalenz, Malte. "Horseshoe RuleFit : Learning Rule Ensembles via Bayesian Regularization." Thesis, Linköpings universitet, Statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-130249.

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This work proposes Hs-RuleFit, a learning method for regression and classification, which combines rule ensemble learning based on the RuleFit algorithm with Bayesian regularization through the horseshoe prior. To this end theoretical properties and potential problems of this combination are studied. A second step is the implementation, which utilizes recent sampling schemes to make the Hs-RuleFit computationally feasible. Additionally, changes to the RuleFit algorithm are proposed such as Decision Rule post-processing and the usage of Decision rules generated via Random Forest. Hs-RuleFit addr
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Beltran, Daniel O. "Model uncertainty and the design of robust monetary policy rules in a small open economy : a Bayesian approach /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2007. http://uclibs.org/PID/11984.

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Crespo, Cuaresma Jesus, Bettina Grün, Paul Hofmarcher, Stefan Humer, and Mathias Moser. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications." WU Vienna University of Economics and Business, 2015. http://epub.wu.ac.at/4493/1/wp193.pdf.

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Posterior analysis in Bayesian model averaging (BMA) applications often includes the assessment of measures of jointness (joint inclusion) across covariates. We link the discussion of jointness measures in the econometric literature to the literature on association rules in data mining exercises. We analyze a group of alternative jointness measures that include those proposed in the BMA literature and several others put forward in the field of data mining. The way these measures address the joint exclusion of covariates appears particularly important in terms of the conclusions that can be dr
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Paranhos, Lívia Silva. "Computing optimal and realised monetary policy rules for Brazil : a markov-switching dsge approach." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/178167.

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A evolução da economia brasileira durante os primeiros anos do século XXI é examinada através de um modelo microfundamentado de uma pequena economia aberta, permitindo mudanças no comportamento do Banco Central do Brasil, no parâmetro de rigidez nominal e na volatilidade dos choques estruturais. Mesmo os resultados não sendo conclusivos a respeito da presença de mudanças de regime durante o período analisado, encontramos evidências de troca de regime no âmbito da política monetária, passando em 2003 de um regime Dove para um regime Hawk, assim como evidências de choques externos mais voláteis
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Kulhavý, Lukáš. "Praktické uplatnění technologií data mining ve zdravotních pojišťovnách." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-77726.

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This thesis focuses on data mining technology and its possible practical use in the field of health insurance companies. Thesis defines the term data mining and its relation to the term knowledge discovery in databases. The term data mining is explained, inter alia, with methods describing the individual phases of the process of knowledge discovery in databases (CRISP-DM, SEMMA). There is also information about possible practical applications, technologies and products available in the market (both products available free and commercial products). Introduction of the main data mining methods a
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Sun, Qi. "Four essays in dynamic macroeconomics." Thesis, St Andrews, 2010. http://hdl.handle.net/10023/941.

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Agli, Hamza. "Raisonnement incertain pour les règles métier." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066129/document.

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Nous étudions dans cette thèse la gestion des incertitudes au sein des systèmes à base de règles métier orientés objet (Object-Oriented Business Rules Management Systems ou OO-BRMS) et nous nous intersessions à des approches probabilistes. Afin de faciliter la modélisation des distributions de probabilités dans ces systèmes, nous proposons d'utiliser les modèles probabilistes relationnels (Probabilistic Relational Models ou PRM), qui sont une extension orientée objet des réseaux bayésiens. Lors de l'exploitation des OO-BRMS, les requêtes adressées aux PRM sont nombreuses et les réponses doiven
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De, Kock Michiel Burger. "From stable priors to maximum Bayesian evidence via a generalised rule of succession." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86545.

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Thesis (PhD)--Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: We investigate the procedure of assigning probabilities to logical statements. The simplest case is that of equilibrium statistical mechanics and its fundamental assumption of equally likely states. Rederiving the formulation led us to question the assumption of logical independence inherent to the construction and speci cally its inability to update probability when data becomes available. Consequently we replace the assumption of logical independence with De Finetti's concept of exchangeability. To use the corresponding
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Books on the topic "Bayesian rules"

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Gubler, Philipp. A Bayesian Analysis of QCD Sum Rules. Springer Japan, 2013. http://dx.doi.org/10.1007/978-4-431-54318-3.

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Gubler, Philipp. A Bayesian Analysis of QCD Sum Rules. Springer Japan, 2013.

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Srivastava, M. S. Optimal bayes stopping rules for detecting the change point in a bernoulli process. University of Toronto, Dept. of Statistics, 1989.

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Bazaldua, Diego A. Luna. Exploring Skill Condensation Rules for Cognitive Diagnostic Models in a Bayesian Framework. [publisher not identified], 2015.

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Mat, Leo. The Bayesian rule: Simplification and geometrical visualization. Roderer, 1998.

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Duo, Qin. Has Bayesian estimation principle ever used Bayes' rule? London University, Queen Mary and Westfield College, Department of Economics, 1994.

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Federico, Sturzenegger, and Harvard University. Center for International Development, eds. Estimating SARB's policy reaction rule. Center for International Development at Harvard University, 2008.

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Bayesian Analysis Of Qcd Sum Rules. Springer Verlag, Japan, 2013.

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Gubler, Philipp. Bayesian Analysis of QCD Sum Rules. Springer Japan, 2015.

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Gubler, Philipp. A Bayesian Analysis of QCD Sum Rules. Springer, 2013.

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Book chapters on the topic "Bayesian rules"

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Johnson, Alicia A., Miles Q. Ott, and Mine Dogucu. "The Big (Bayesian) Picture." In Bayes Rules! Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9780429288340-1.

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Johnson, Alicia A., Miles Q. Ott, and Mine Dogucu. "The Beta-Binomial Bayesian Model." In Bayes Rules! Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9780429288340-3.

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Johnson, Alicia A., Miles Q. Ott, and Mine Dogucu. "Balance and Sequentiality in Bayesian Analyses." In Bayes Rules! Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9780429288340-4.

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Howson, Colin. "Bayesian Rules of Updating." In Probability, Dynamics and Causality. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5712-4_4.

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Xie, Zhipeng. "Boosting Local Naïve Bayesian Rules." In Advances in Neural Networks – ISNN 2009. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01510-6_87.

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Oaksford, Mike, and Ulrike Hahn. "Why Are We Convinced by the Ad Hominem Argument?: Bayesian Source Reliability and Pragma-Dialectical Discussion Rules." In Bayesian Argumentation. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5357-0_3.

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Marques, Ricardo, Christian Bouville, Kadi Bouatouch, and Luís Paulo Santos. "Bayesian Monte Carlo for Global Illumination." In Efficient Quadrature Rules for Illumination Integrals. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-031-79567-1_3.

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Gubler, Philipp. "Basics of QCD Sum Rules." In A Bayesian Analysis of QCD Sum Rules. Springer Japan, 2013. http://dx.doi.org/10.1007/978-4-431-54318-3_3.

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Webb, Geoffrey I. "Candidate Elimination Criteria for Lazy Bayesian Rules." In AI 2001: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45656-2_47.

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Kachiashvili, K. J. "Constrained Bayesian Rules for Testing Statistical Hypotheses." In Strategic Management, Decision Theory, and Decision Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1368-5_11.

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Conference papers on the topic "Bayesian rules"

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Savell, C. Thomas, Bob Baboian, Russ Kane, et al. "Intelligent Agents for Corrosion Prevention in New Vehicle Design." In CORROSION 2003. NACE International, 2003. https://doi.org/10.5006/c2003-03218.

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Abstract This paper describes the development of an expert tool for vehicle design that assists the designer in avoiding bad design decisions, which may cause corrosion problems during the life of the vehicle. The tool is an autonomous agent installed as part of designer's CAD/CAE system. It uses a Hybrid Expert Production System containing Rules in its Knowledge Base and both an Inference Engine that compares these stored Rules with the information (Facts) provided by the designer and CAD/CAE software and a Bayesian Network for processing uncertainty in the facts and rules. An important enhan
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Yu, Xiaochen, Hua Rong, Yanmin Sun, and Dawei Zhang. "Method for Assessing the Operational State of Transformers Based on Association Rule Mining and Bayesian Network." In 2024 3rd International Conference on Energy and Electrical Power Systems (ICEEPS). IEEE, 2024. http://dx.doi.org/10.1109/iceeps62542.2024.10693108.

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Firmino, Paulo Renato A., and Ademir B. dos Santos Neto. "Essays on probability elicitation scoring rules." In XI BRAZILIAN MEETING ON BAYESIAN STATISTICS: EBEB 2012. AIP, 2012. http://dx.doi.org/10.1063/1.4759598.

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Eick, Christoph F., and Daw Jong. "Learning Bayesian classification rules through genetic algorithms." In the second international conference. ACM Press, 1993. http://dx.doi.org/10.1145/170088.170157.

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Gubler, Philipp, and Makoto Oka. "A Bayesian analysis of QCD sum rules." In THE IX INTERNATIONAL CONFERENCE ON QUARK CONFINEMENT AND THE HADRON SPECTRUM—QCHS IX. AIP, 2011. http://dx.doi.org/10.1063/1.3575024.

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Goldwater, Sharon, and Mark Johnson. "Priors in Bayesian learning of phonological rules." In the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology. Association for Computational Linguistics, 2004. http://dx.doi.org/10.3115/1622153.1622158.

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Davis, Jesse, Elizabeth Burnside, David Page, Inês Dutra, and Vítor Santos Costa. "Learning Bayesian networks of rules with SAYU." In the 4th international workshop. ACM Press, 2005. http://dx.doi.org/10.1145/1090193.1090196.

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Kudlicki, Andrzej. "Stereochemical rules for connecting disjoint protein fragments." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 24th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2004. http://dx.doi.org/10.1063/1.1835211.

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Wang, Peng, Nidhal C. Bouaynaya, Lyudmila Mihaylova, Jikai Wang, Qibin Zhang, and Renke He. "Bayesian Neural Networks Uncertainty Quantification with Cubature Rules." In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9207214.

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Thirumuruganathan, Saravanan, and Manfred Huber. "Building Bayesian Network based expert systems from rules." In 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2011. http://dx.doi.org/10.1109/icsmc.2011.6084157.

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Reports on the topic "Bayesian rules"

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Hajdini, Ina. Mis-specified Forecasts and Myopia in an Estimated New Keynesian Model. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202203r.

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The paper considers a New Keynesian framework in which agents form expectations based on a combination of autoregressive mis-specified forecasts and myopia. The proposed expectations formation process is shown to be consistent with all three empirical facts on consensus inflation forecasts. However, while mis-specified forecasts can be both sufficient and necessary to match all three facts, myopia alone is neither. The paper then derives the general equilibrium solution consistent with the proposed expectations formation process and estimates the model with likelihood-based Bayesian methods, y
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Granados, Camilo, and Daniel Parra-Amado. Output Gap Measurement after COVID for Colombia: Lessons from a Permanent-Transitory Approach. Banco de la República, 2025. https://doi.org/10.32468/be.1295.

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We estimate the output gap for the Colombian economy explicitly accounting for the COVID-19 period. Our estimates reveal a significant $20$\% decline in the output gap but with a faster recovery compared to previous crises. Our empirical strategy follows a two-stage Bayesian vector autoregressive (BSVAR) model where i) a scaling factor in the reduced form of VAR is used to model extreme data, such as those observed around the COVID-19 period, and ii) permanent and transitory shocks are structurally identified. As a result, we obtain that a single structural shock explains the potential GDP, wh
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