Relevant bibliographies by topics / Bayes's method

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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 'Bayes's method'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Bayes's method"

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Wahyunita, Laili. "Klasifikasi Penyebab Penyalahgunaan Narkoba Dari Berita Online Dengan Menggunakan Naive Bayes." Jurnal ELTIKOM 1, no. 1 (2017): 23–30. http://dx.doi.org/10.31961/eltikom.v1i1.12.

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This research conducted the classification process by applying the method of classification of Naive Bayes. News article document is one form of text data that is not structured so that requires the process of cleaning data and pre-processing first. The Naive Bayes approach is an approach that refers to Bayes's Theorem, where it uses the principle of statistical opportunity to combine previous knowledge. The use of this technique is based on the need of the system to know the probability value of the data to be classified. Waterfall method was used for built this classificaiton system. Accurac
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Utyuganova, V. V., V. S. Serdyuk, and A. I. Fomin. "Prediction and Assessment of the Occupational Risks in the Mining Industry Using the Bayess Theorem." Occupational Safety in Industry, no. 1 (January 2021): 79–87. http://dx.doi.org/10.24000/0409-2961-2021-1-79-87.

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The analysis of existing methods for assessing occupational risks is carried out, and the need for searchinga fundamentally new approach to the assessment and prediction of risks in the mining industry is substantiated. Based on the results of the analysis of modern methods and technologies, it is established that the development of the methodology for assessment and prediction of the occupational risks using Bayes's theorem has significant advantages: simplicity and accessibility for the occupational safety specialists, reproducibility considering many factors of working conditions, as well a
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Zavadskas, Edmundas Kazimieras, Leonas Ustinovičius, Zenonas Turskis, Friedel Peldschus, and Danny Messing. "LEVI 3.0—MULTIPLE CRITERIA EVALUATION PROGRAM FOR CONSTRUCTION SOLUTIONS." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 8, no. 3 (2002): 184–91. http://dx.doi.org/10.3846/13923730.2002.10531275.

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The paper considers the main methods employed to solve one-sided and two-sided problems of the game theory. For the one-sided problems only the method of solution “distance to the ideal point” is discussed. For the two-sided problems a distinction is made between games with rational behaviour and games against nature. The main principles of the strategies are as follows: simple min-max principle, extended min-max principle, Wald's rule, Savage criterion, Hurwicz's rule, Laplace's rule, Bayes's rule, Hodges-Lehmann rule. The questions transforming the decisionmaking matrix are considered: vecto
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Imai, Kosuke, and Kabir Khanna. "Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records." Political Analysis 24, no. 2 (2016): 263–72. http://dx.doi.org/10.1093/pan/mpw001.

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In both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geoco
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Jevning, R., R. Anand, and M. Biedebach. "Certainty and uncertainty in science: the subjectivistic concept of probability in physiology and medicine." Advances in Physiology Education 267, no. 6 (1994): S113. http://dx.doi.org/10.1152/advances.1994.267.6.s113.

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Most physiological scientists have restricted understanding of probability as relative frequency in a large collection (for example, of atoms). Most appropriate for the relatively circumscribed problems of the physical sciences, this understanding of probability as a physical property has conveyed the widespread impression that the "proper" statistical "method" can eliminate uncertainty by determining the "correct" frequency or frequency distribution. However, many relatively recent developments in the theory of probability and decision making deny such exalted statistical ability. Proponents
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Pang, Xun. "Modeling Heterogeneity and Serial Correlation in Binary Time-Series Cross-sectional Data: A Bayesian Multilevel Model with AR(p) Errors." Political Analysis 18, no. 4 (2010): 470–98. http://dx.doi.org/10.1093/pan/mpq019.

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This paper proposes a Bayesian generalized linear multilevel model with apth-order autoregressive error process to analyze unbalanced binary time-series cross-sectional (TSCS) data. The model specification is motivated by the generic TSCS data structure and is intended to handle the associated inefficiency and endogeneity problems. It accommodates heterogeneity across units and between time periods in the form of random intercepts and random-effect coefficients. At the same time, itspth-order autoregressive error process, employed either by itself or in concert with other dynamic methods, adeq
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Legiawati, Nenden, Teguh Iman Hermanto, and Yudhi Raymond Ramadhan. "Analisis Sentimen Opini Pengguna Twitter Terhadap Perusahaan Jasa Ekspedisi Menggunakan Algoritma Naïve Bayes Berbasis PSO." JURIKOM (Jurnal Riset Komputer) 9, no. 4 (2022): 930. http://dx.doi.org/10.30865/jurikom.v9i4.4629.

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Expeditions are used in the process of delivering goods or selling them remotely. Twitter has become a social media for information sharing and opinions, including those on the expeditionary services both negative and positive. The solution for the problem which occurs is that of sentiment analysis, helpful in grouping the data and predicting the tweet. The aim of the research to predict sentient tweeted data using a file classification method, naive bayes's algorithm calculated the value of the tweets of the Anteraja expedition service that had the results accuracy 87,77%, precision 76,67%, r
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Peter, Justin R., Alan Seed, and Peter J. Steinle. "Application of a Bayesian Classifier of Anomalous Propagation to Single-Polarization Radar Reflectivity Data." Journal of Atmospheric and Oceanic Technology 30, no. 9 (2013): 1985–2005. http://dx.doi.org/10.1175/jtech-d-12-00082.1.

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Abstract A naïve Bayes classifier (NBC) was developed to distinguish precipitation echoes from anomalous propagation (anaprop). The NBC is an application of Bayes's theorem, which makes its classification decision based on the class with the maximum a posteriori probability. Several feature fields were input to the Bayes classifier: texture of reflectivity (TDBZ), a measure of the reflectivity fluctuations (SPIN), and vertical profile of reflectivity (VPDBZ). Prior conditional probability distribution functions (PDFs) of the feature fields were constructed from training sets for several meteor
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Harries, R. W. J. "A Rational Approach to Radiological Screening in Von Hippel-Lindau Disease." Journal of Medical Screening 1, no. 2 (1994): 88–95. http://dx.doi.org/10.1177/096914139400100205.

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Objectives— To optimise radiological screening in von Hippel-Lindau disease (VHL) while minimising cost and morbidity. Methods— A model of VHL was based on retrospective studies, and Bayes's theorem used to calculate the probability of the gene's presence and the likelihood of further lesions in affected families. A six year follow up was conducted to test the validity of the model. Results— Follow up confirmed the accuracy and validity of the model. Posterior fossa haemangioblastomas occur in 79·2% of VHL cases, supratentorial, retinal and spinal haemangioblastomas in 6·9%, 42·8%, and 22·0%,
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Lee, Kyeongjun. "Bayes and Maximum Likelihood Estimation of Uncertainty Measure of the Inverse Weibull Distribution under Generalized Adaptive Progressive Hybrid Censoring." Mathematics 10, no. 24 (2022): 4782. http://dx.doi.org/10.3390/math10244782.

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The inverse Weibull distribution (IWD) can be applied to a various situations, including applications in reliability and medicine. In a reliability and medicine test, it is generally known that the results of test units may not be recorded. Recently, the generalized adaptive progressive hybrid censoring (GAPHC) scheme was introduced. In this paper, therefore, we consider the classical estimators (maximum likelihood estimator (MLE) and maximum product spacings estimator (MPSE)) and Bayes estimators (BayEsts) of the uncertainty measure of the IWD under GAPHC scheme. We derive the BayEsts of the
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Dissertations / Theses on the topic "Bayes's method"

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Benhaddou, Rida. "Nonparametric and Empirical Bayes Estimation Methods." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5765.

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In the present dissertation, we investigate two different nonparametric models; empirical Bayes model and functional deconvolution model. In the case of the nonparametric empirical Bayes estimation, we carried out a complete minimax study. In particular, we derive minimax lower bounds for the risk of the nonparametric empirical Bayes estimator for a general conditional distribution. This result has never been obtained previously. In order to attain optimal convergence rates, we use a wavelet series based empirical Bayes estimator constructed in Pensky and Alotaibi (2005). We prop
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Brandel, John. "Empirical Bayes methods for missing data analysis." Thesis, Uppsala University, Department of Mathematics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121408.

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Lönnstedt, Ingrid. "Empirical Bayes Methods for DNA Microarray Data." Doctoral thesis, Uppsala University, Department of Mathematics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5865.

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<p>cDNA microarrays is one of the first high-throughput gene expression technologies that has emerged within molecular biology for the purpose of functional genomics. cDNA microarrays compare the gene expression levels between cell samples, for thousands of genes simultaneously. </p><p>The microarray technology offers new challenges when it comes to data analysis, since the thousands of genes are examined in parallel, but with very few replicates, yielding noisy estimation of gene effects and variances. Although careful image analyses and normalisation of the data is applied, traditional metho
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Lönnstedt, Ingrid. "Empirical Bayes methods for DNA microarray data /." Uppsala : Matematiska institutionen, Univ. [distributör], 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5865.

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Amiss, Julie E. "Bayes factors : comparisons, simulation methods and influence." Thesis, University of Surrey, 1996. http://epubs.surrey.ac.uk/1014/.

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Qian, Wendi. "Bayes methods in group sequential clinical trials." Thesis, University of Kent, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263693.

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Guez, A. G. "Sample-based search methods for Bayes-adaptive planning." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1462170/.

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A fundamental issue for control is acting in the face of uncertainty about the environment. Amongst other things, this induces a trade-off between exploration and exploitation. A model-based Bayesian agent optimizes its return by maintaining a posterior distribution over possible environments, and considering all possible future paths. This optimization is equivalent to solving a Markov Decision Process (MDP) whose hyperstate comprises the agent's beliefs about the environment, as well as its current state in that environment. This corresponding process is called a Bayes-Adaptive MDP (BAMDP).
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Smith, James A. "“Looking for nothing" : Bayes linear methods for solving equations." Thesis, Durham University, 1993. http://etheses.dur.ac.uk/2207/.

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Here I will describe and implement Bayes linear methods for finding zeros of deterministic functions. We assume that the zero is known to be unique. Initially, the value of the function is modelled simply as the product of two independent factors, the position of the point from the zero and a "slope" which is assumed to vary "smoothly” with position. Additional prior information specifies first and second order properties of the slopes and the position of the zero: in particular, smoothness is specified by modelling the slope process to be stationary with a decreasing correlation function. Thi
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Jakimauskas, Gintautas. "Analysis and application of empirical Bayes methods in data mining." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140423_090853-72998.

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The research object is data mining empirical Bayes methods and algorithms applied in the analysis of large populations of large dimensions. The aim and objectives of the research are to create methods and algorithms for testing nonparametric hypotheses for large populations and for estimating the parameters of data models. The following problems are solved to reach these objectives: 1. To create an efficient data partitioning algorithm of large dimensional data. 2. To apply the data partitioning algorithm of large dimensional data in testing nonparametric hypotheses. 3. To apply the empirical
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Everitt, Niklas. "Module identification in dynamic networks: parametric and empirical Bayes methods." Doctoral thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208920.

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The purpose of system identification is to construct mathematical models of dynamical system from experimental data. With the current trend of dynamical systems encountered in engineering growing ever more complex, an important task is to efficiently build models of these systems. Modelling the complete dynamics of these systems is in general not possible or even desired. However, often, these systems can be modelled as simpler linear systems interconnected in a dynamic network. Then, the task of estimating the whole network or a subset of the network can be broken down into subproblems of est
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Books on the topic "Bayes's method"

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Maritz, J. S. Empirical Bayes methods. 2nd ed. Chapman and Hall, 1989.

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author, Lwin T., ed. Empirical Bayes Methods. Taylor and Francis, 2018.

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Carlin, Bradley P. Bayes and empirical Bayes methods for data analysis. Chapman & Hall/CRC, 1998.

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1944-, Louis Thomas A., ed. Bayes and empirical Bayes methods for data analysis. Chapman & Hall, 1996.

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Carlin, Bradley P. Bayes and Empirical Bayes methods for data analysis. 2nd ed. Chapman & Hall/CRC, 2000.

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Šmídl, Václav. The variational Bayes method in signal processing. Springer, 2006.

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Maximum Entropy Workshop (8th 1988 St. John's College). Maximum entropy and Bayesian methods, Cambridge, England, 1988. Kluwer Academic Publishers, 1989.

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Wakefield, Jon. Bayesian and Frequentist Regression Methods. Springer New York, 2013.

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Press, S. James. Bayesian statistics: Principles, models, and applications. Wiley, 1989.

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Lawson, Andrew. Bayesian disease mapping: Hierarchical modeling in spatial epidemiology. Taylor & Francis, 2008.

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Book chapters on the topic "Bayes's method"

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King, David, Nadeeshani Wanigarathna, Keith Jones, and Joseph Ofori-Kuragu. "A Systematic Literature Review to Identify a Methodological Approach for Use in the Modelling and Forecasting of Capital Expenditure of Hyperscale Data Centres." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.37.

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The theme of ‘Managing the digital transformation of the construction industry’ emphasises the importance of considering various dimensions of digitalisation and optimising the built environment. This review aims to present methodological approaches from existing literature that elucidate location-related factors impacting the capital cost of data centres. These findings facilitate adjustments to historical cost data when estimating total costs for new data centres. A systematic literature review method was employed to ensure an objective and comprehensive synthesis. In conjunction with Bayes'
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King, David, Nadeeshani Wanigarathna, Keith Jones, and Joseph Ofori-Kuragu. "A Systematic Literature Review to Identify a Methodological Approach for Use in the Modelling and Forecasting of Capital Expenditure of Hyperscale Data Centres." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.37.

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The theme of ‘Managing the digital transformation of the construction industry’ emphasises the importance of considering various dimensions of digitalisation and optimising the built environment. This review aims to present methodological approaches from existing literature that elucidate location-related factors impacting the capital cost of data centres. These findings facilitate adjustments to historical cost data when estimating total costs for new data centres. A systematic literature review method was employed to ensure an objective and comprehensive synthesis. In conjunction with Bayes'
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Isermann, Rolf. "Bayes-Methode." In Identifikation dynamischer Systeme 2. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84769-1_2.

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Isermann, Rolf. "Bayes-Methode." In Identifikation dynamischer Systeme. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-97069-6_2.

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Li, Hang. "The Naïve Bayes Method." In Machine Learning Methods. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3917-6_4.

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Yasuda, Muneki. "Empirical Bayes Method for Boltzmann Machines." In Sublinear Computation Paradigm. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4095-7_11.

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AbstractThe framework of the empirical Bayes method allows the estimation of the values of the hyperparameters in the Boltzmann machine by maximizing a specific likelihood function referred to as the empirical Bayes likelihood function. However, the maximization is computationally difficult because the empirical Bayes likelihood function involves intractable integrations of the partition function. The method presented in this chapter avoids this computational problem by using the replica method and the Plefka expansion, which is quite simple and fast because it does not require any iterative p
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Montesinos López, Osval Antonio, Abelardo Montesinos López, and Jose Crossa. "Bayesian Genomic Linear Regression." In Multivariate Statistical Machine Learning Methods for Genomic Prediction. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89010-0_6.

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AbstractThe Bayesian paradigm for parameter estimation is introduced and linked to the main problem of genomic-enabled prediction to predict the trait of interest of the non-phenotyped individuals from genotypic information, environment variables, or other information (covariates). In this situation, a convenient practice is to include the individuals to be predicted in the posterior distribution to be sampled. We explained how the Bayesian Ridge regression method is derived and exemplified with data from plant breeding genomic selection. Other Bayesian methods (Bayes A, Bayes B, Bayes C, and
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Savchuk, Vladimir, and Chris P. Tsokos. "The Accepted Bayes Method of Estimation." In Bayesian Theory and Methods with Applications. Atlantis Press, 2011. http://dx.doi.org/10.2991/978-94-91216-14-5_2.

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Vidakovic, Brani. "Wavelet-Based Nonparametric Bayes Methods." In Practical Nonparametric and Semiparametric Bayesian Statistics. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-1732-9_7.

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Efron, Bradley. "Empirical Bayes: Concepts and Methods." In Handbook of Bayesian, Fiducial, and Frequentist Inference. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9780429341731-2.

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Conference papers on the topic "Bayes's method"

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Choe, Do Kook, and Eugene Charniak. "Naive Bayes Word Sense Induction." In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2013. http://dx.doi.org/10.18653/v1/d13-1148.

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Heineman, David, Yao Dou, and Wei Xu. "Improving Minimum Bayes Risk Decoding with Multi-Prompt." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.1255.

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Deguchi, Hiroyuki, Yusuke Sakai, Hidetaka Kamigaito, and Taro Watanabe. "mbrs: A Library for Minimum Bayes Risk Decoding." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-demo.37.

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Skilling, John. "Bayesics." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2005. http://dx.doi.org/10.1063/1.2149776.

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Azeraf, Elie, Emmanuel Monfrini, and Wojciech Pieczynski. "Improving Usual Naive Bayes Classifier Performances with Neural Naive Bayes based Models." In 11th International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0010890400003122.

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Xu, Yuhan, and Sheng Fang. "Comparison Between Different Source Reconstruction Methods of Atmospheric Leakages." In ASME 2023 International Conference on Environmental Remediation and Radioactive Waste Management. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/icem2023-109865.

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Abstract When a severe nuclear accident occurs, the diffusion and transportation of airborne radioactive materials can cause harmful effects on the public. An accurate source release rate assessment is necessary to evaluate the consequence of the accident. Provided the leakage source location is known, the source inversion method can inversely estimate the release rate by coupling environmental measurements and the atmospheric dispersion model. Since the Fukushima nuclear accident, source inversion has significantly progressed over the past decade. However, the recent accidental radionuclide l
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Price, Harold J. "Uninformative priors for Bayes’ theorem." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING. AIP, 2002. http://dx.doi.org/10.1063/1.1477060.

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Xiao, Mi, Qiangzhuang Yao, Liang Gao, Haihong Xiong, and Fengxiang Wang. "Metamodel Uncertainty Quantification by Using Bayes’ Theorem." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46746.

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In complex engineering systems, approximation models, also called metamodels, are extensively constructed to replace the computationally expensive simulation and analysis codes. With different sample data and metamodeling methods, different metamodels can be constructed to describe the behavior of an engineering system. Then, metamodel uncertainty will arise from selecting the best metamodel from a set of alternative ones. In this study, a method based on Bayes’ theorem is used to quantify this metamodel uncertainty. With some mathematical examples, metamodels are built by six metamodeling met
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Luengo, J., and Rafael Rumi. "Naive Bayes Classifier with Mixtures of Polynomials." In International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005166000140024.

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"Naïve Bayes Domain Adaptation for Biological Sequences." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004245500620070.

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Reports on the topic "Bayes's method"

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Gupta, Shanti S., and Jinjun Lu. Empirical Bayes Estimation With Kernel Sequence Method. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada396449.

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Walters, Christopher. Empirical Bayes Methods in Labor Economics. National Bureau of Economic Research, 2024. http://dx.doi.org/10.3386/w33091.

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Carlin, Bradley P., and Alan E. Gelfand. A Sample Reuse Method for Accurate Parametric Empirical Bayes Confidence Intervals. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada216198.

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Gu, Jiaying, and Roger Koenker. Rebayes: an R package for empirical bayes mixture methods. The IFS, 2017. http://dx.doi.org/10.1920/wp.cem.2017.3717.

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McPhedran, R., K. Patel, B. Toombs, et al. Food allergen communication in businesses feasibility trial. Food Standards Agency, 2021. http://dx.doi.org/10.46756/sci.fsa.tpf160.

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Background: Clear allergen communication in food business operators (FBOs) has been shown to have a positive impact on customers’ perceptions of businesses (Barnett et al., 2013). However, the precise size and nature of this effect is not known: there is a paucity of quantitative evidence in this area, particularly in the form of randomised controlled trials (RCTs). The Food Standards Agency (FSA), in collaboration with Kantar’s Behavioural Practice, conducted a feasibility trial to investigate whether a randomised cluster trial – involving the proactive communication of allergen information a
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