Search Results - Bayesian decision theory

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  1. 1

    Statistical decision theory and Bayesian analysis / by Berger, James O.

    Published 1985
    Subjects:
    Book
  2. 2

    Bayesian models in economic theory

    Published 1984
    Subjects: “…Bayesian statistical decision theory…”
    Book
  3. 3

    Bayesian statistics : an introduction / by Lee, Peter M.

    Published 1989
    Subjects: “…Bayesian statistical decision theory.…”
    Book
  4. 4

    An introduction to Bayesian inference in econometrics by Zellner, Arnold

    Published 1971
    Subjects:
    Book
  5. 5

    Bayesian approach to global optimization : theory and applications / by Mockus, Jonas

    Published 1989
    Subjects:
    Book
  6. 6

    Bayesian analysis of linear models by Broemeling, Lyle D., 1939-

    Published 1985
    Subjects:
    Book
  7. 7

    Decision analysis with business applications by Tummala, V. M. Rao

    Published 1973
    Subjects:
    Book
  8. 8

    Rational descriptions, decisions, and designs / by Tribus, Myron

    Published 1969
    Subjects: “…Bayesian statistical decision theory.…”
    Book
  9. 9

    Probability, statistics, and decision for civil engineers by Benjamin, Jack R.

    Published 1970
    Subjects:
    Book
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    The economics of uncertainty / by Borch, Karl Henrik

    Published 1968
    Subjects:
    Book
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    Information‐Theoretic Scores for Bayesian Model Selection and Similarity Analysis: Concept and Application to a Groundwater Problem by Maria Fernanda Morales Oreamuno, Sergey Oladyshkin, Wolfgang Nowak

    Published 2023-07-01
    “…Exploring the connection between Bayesian inference and information theory, we explicitly link BME and ELPD together with RE and IE to highlight the information flow in BMS and BMJ analyses. …”
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    Bayesian adaptive trials for social policy by Sally Cripps, Anna Lopatnikova, Hadi Mohasel Afshar, Ben Gales, Roman Marchant, Gilad Francis, Catarina Moreira, Alex Fischer

    Published 2025-01-01
    “…Recognizing the crucial need for evidence-based approaches in public policy, the proposed approach aims to lower barriers to the adoption of evidence-based methods and to align evaluation processes more closely with the dynamic nature of policy cycles. BATs, grounded in decision theory, offer a dynamic, “learning as we go” approach, enabling the integration of diverse information types and facilitating a continuous, iterative process of policy evaluation. …”
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    Article
  16. 16

    A Strategic Hydrogen Supplier Assessment Using a Hybrid MCDA Framework with a Game Theory-Driven Criteria Analysis by Jettarat Janmontree, Aditya Shinde, Hartmut Zadek, Sebastian Trojahn, Kasin Ransikarbum

    Published 2025-07-01
    “…This study proposes a novel hybrid MCDA framework that integrates the Bayesian Best–Worst Method (BWM), Fuzzy Analytic Hierarchy Process (AHP), and Entropy Weight Method (EWM) for robust criteria weighting, which is aggregated using a game theory-based model to resolve inconsistencies and capture the complementary strengths of each technique. …”
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    Article
  17. 17

    Analyzing water footprint and water resources sustainability in China’s arid Northwest with Bayesian network by Lingyun Zhang, Lingxiao Sun, Yang Yu, Xiaoyun Ding, Zengkun Guo, Ruide Yu

    Published 2025-08-01
    “…To promote the sustainable development of both the economy and water resources, this study integrates the water footprint (WF) theory with a Bayesian network (BN) model to probabilistically characterize the uncertainties of influencing factors in water sustainability assessment, thus providing a flexible and effective decision-support tool. …”
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    Article
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    Bayesian-Optimized Multi-Task Gaussian Process Regression With Composite Kernels for Soybean Oil Futures Forecasting by Hui-Dong Yin, Yi-Yang Li

    Published 2025-01-01
    “…The framework incorporates futures market indicators and employs spectral analysis with Reproducing Kernel Hilbert Space (RKHS) theory for feature alignment. Using a decade-long dataset (2015–2024) of daily soybean oil prices, the model undergoes rigorous validation via cross-validated Bayesian optimization, bootstrap error estimation, and posterior predictive intervals. …”
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    Article
  20. 20

    NEURAL NETWORK MODEL OF DIAGNOSTICS OF STAGES OF DEVELOPING CORPORATE BANKRUPTCY by S. A. Gorbatkov, S. A. Farkhieva

    Published 2018-06-01
    “…The model should serve as a tool for improving the objectivity and quality of decisions on the restructuring of corporate debt. The study was conducted on the basis of neural network modelling and system analysis methods, methods of decision-making theory, a solution of inverse problems of interpretation, i.e. extraction of new knowledge from data. …”
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