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Bayesian Update with Information Quality under the Framework of Evidence Theory
Entropy, 2018 Bayesian update is widely used in data fusion. However, the information quality is not taken into consideration in classical Bayesian update method. In this paper, a new Bayesian update with information quality under the framework of evidence theory is ...
Yuting Li, Fuyuan Xiao
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Simultaneous probability statements for Bayesian P-splines [PDF]
, 2005 P-splines are a popular approach for fitting nonlinear effects of continuous covariates in semiparametric regression models. Recently, a Bayesian version for P-splines has been developed on the basis of Markov chain Monte Carlo simulation techniques for
Brezger, Andreas, Lang, S.
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Market Structure and Competition in the Indian Microfinance Sector
Vikalpa, 2019 Executive Summary The Indian microfinance sector has experienced fundamental changes in the structure of ownership and management of microfinance institutions (MFIs).
Nitin Navin, Pankaj Sinha
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A Probability-based Evolutionary Algorithm with Mutations to Learn Bayesian Networks
International Journal of Interactive Multimedia and Artificial Intelligence, 2014 Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that ...
Sho Fukuda +2 more
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Fault diagnosis of mine drainage system based on fuzzy Bayesian network
Gong-kuang zidonghua, 2022 The mine drainage system is developing towards automation and intelligence. The system's structure and function are becoming more and more complex, and the abnormal function and failure of a single component may cause the failure of the whole system. The
SHI Xiaojuan, YAO Bing, GU Huabei
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, 2000 After making some general remarks, I consider two examples that illustrate the use of Bayesian Probability Theory. The first is a simple one, the physicist's favorite "toy," that provides a forum for a discussion of the key conceptual issue of Bayesian ...
Prosper, Harrison B.
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Randomization-based, Bayesian inference of causal effects
Journal of Causal Inference, 2023 Bayesian causal inference in randomized experiments usually imposes model-based structure on potential outcomes. Yet causal inferences from randomized experiments are especially credible because they depend on a known assignment process, not a ...
Leavitt Thomas
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Clinical and Translational Science, 2023 In this study, we aimed to evaluate limited sampling strategies for achieving the therapeutic ranges of the area under the concentration‐time curve (AUC) of vancomycin on the first and second day (AUC0–24, AUC24–48, respectively) of therapy.
Kazutaka Oda +9 more
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Bayesian retrieval of complete posterior PDFs of oceanic rain rate from microwave observations [PDF]
, 2006 A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR).
Adler +32 more
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Frontiers in Psychology, 2016 Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design ...
Moritz eBoos +3 more
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