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A Comprehensive Review and Application of bayesian methods in Hydrological Modelling: Past, Present, and Future Directions

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WATER 2025年第7期17卷

作者： Haddad, Khaled Western Sydney Univ Sch Engn Design & Built Environm Off XB-3-43Kingswood Penrith Campus Penrith NSW 1797 Australia

bayesian methods have revolutionised hydrological modelling by providing a framework for managing uncertainty, improving model calibration, and enabling more accurate predictions. This paper reviews the evolution of bayesian methods in hydrology, from their initial applications in flood-frequency analysis to their current use in streamflow forecasting, flood risk assessment, and climate-change adaptation. It discusses the development of key bayesian techniques, such as Markov Chain Monte Carlo (MCMC) methods, hierarchical models, and approximate bayesian computation (ABC), and their integration with remote sensing and big data analytics. The paper also presents simulated examples demonstrating the application of bayesian methods to flood, drought, and rainfall data, showcasing the potential of these methods to inform water-resource management, flood risk mitigation, and drought prediction. The future of bayesian hydrology lies in expanding the use of machine learning, improving computational efficiency, and integrating large-scale datasets from remote sensing. This review serves as a resource for hydrologists seeking to understand the evolution and future potential of bayesian methods in addressing complex hydrological challenges.

关键词： bayesian methods hydrological modelling uncertainty quantification flood forecasting machine learning integration climate-change impact

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Priors and decision thresholds in phase 2 and phase 3 randomized controlled trials evaluating drug efficacy using bayesian methods: a systematic review

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JOURNAL OF CLINICAL EPIDEMIOLOGY 2025年 179卷 111651-111651页

作者： Barret, Lorraine Liaigre, Lea Hlavaty, Alex Giai, Joris Laporte, Silvy Ollier, Edouard Meyer, Nicolas Khouri, Charles Cucherat, Michel Roustit, Matthieu Univ Grenoble Alpes INSERM CHU Grenoble Alpes CIC 1406 F-38000 Grenoble France Univ Grenoble Alpes INSERM HP2 U1300 F-38000 Grenoble France Univ Grenoble Alpes CNRS UMR 5525 VetAgro SupGrenoble INPTIMC F-38000 Grenoble France Univ Jean Monnet Serv Pharmacol Clin Mines St Etienne INSERMU1059SainbioseCHU St Etienne F-42023 St Etienne France Hop Univ Strasbourg Pole Sante Publ GMRC Strasbourg France Hosp Civils Lyon Metaevidence Org Serv Pharmacol & Toxicol F-69000 Lyon France

Objectives: To describe the priors and decision thresholds in phase 2 and 3 randomized controlled trials (RCTs) evaluating drug efficacy using bayesian methods. Study Design and Setting: A systematic review of phase 2 and 3 RCTs evaluating drug efficacy through bayesian inference was conducted across the MEDLINE, EMBASE, and Cochrane databases, with no date restrictions until September 2022. The type of prior used for the analysis of the primary endpoint and its characteristics (type and parameters of the distribution, justification, and sensitivity analysis), the use of a posterior probability decision threshold defined a priori, and its value, were extracted. Results: From 1161 articles screened, 69 articles were ultimately included, encompassing a total of 91 comparisons, as some trials assessed multiple primary endpoints or treatments. The prior was assigned to treatment effect in 51% of the cases (n = 46) to each arm in 37% (n = 34) and was not explicitly defined in 12% (n = 11). Prior distribution was described (with its parameters) in 59% of cases (n = 54). A decision threshold was set a priori in 68% of the results (n = 62), and its value ranged from 70% to 99% (median 95%). Conclusion: The inconsistent description of priors, along with the wide variation and occasional absence of decision thresholds, underscore the need for clear guidelines on the use and reporting of bayesian methods. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： bayesian methods Randomized controlled trials Drug efficacy Priors Decision thresholds Reporting standards

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bayesian methods for the conformational classification of eight-membered rings

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ACTA CRYSTALLOGRAPHICA SECTION B-STRUCTURAL SCIENCE CRYSTAL ENGINEERING AND MATERIALS 2005年第5期61卷 585-594页

作者： Pérez, J Nolsoe, K Kessler, M García, L Pérez, E Serrano, JL Univ Politecn Cartagena Area Quim Inorgan Dept Ingn Minera Geol & Cartografica Cartagena Spain Univ Politecn Cartagena Dept Matemat Aplicada & Estadistica Cartagena Spain

Two methods for the classification of eight-membered rings based on a bayesian analysis are presented. The two methods share the same probabilistic model for the measurement of torsion angles, but while the first method uses the canonical forms of cyclooctane and, given an empirical sequence of eight torsion angles, yields the probability that the associated structure corresponds to each of the ten canonical conformations, the second method does not assume previous knowledge of existing conformations and yields a clustering classification of a data set, allowing new conformations to be detected. Both methods have been tested using the conformational classification of Csp(3) eight-membered rings described in the literature. The methods have also been employed to classify the solid-state conformation in Csp(3) eight-membered rings using data retrieved from an updated version of the Cambridge Structural Database (CSD).

关键词： bayesian methods conformational classification canonical conformations clustering.

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bayesian methods for control loop monitoring and diagnosis

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JOURNAL OF PROCESS CONTROL 2008年第9期18卷 829-838页

作者： Huang, Biao Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 2G6 Canada

There exist many algorithms for control performance monitoring. There are also many algorithms available for process monitoring. There are, however, few methods available for synthesis of various monitoring techniques to form a diagnosing system for optimal decision making. This paper is concerned with establishing and demonstrating a novel probabilistic diagnostic framework for control loop monitoring. The new framework possesses a number of desired properties, including, for example, quantitative probabilistic diagnosis, flexibility in synthesizing different monitoring techniques, robustness in the presence of missing data or missing variables, ease of expanding or shrinking the diagnosing system, ability to incorporate a priori process knowledge, and capability for decision making. As the backbone of the proposed framework, the emerging bayesian methods are introduced and shown to be the appropriate tools for solving the problem of concern. Several representative control loop diagnostic problems are formulated under the bayesian framework and their solutions are demonstrated through examples. The experiences and challenges learned from industrial applications of bayesian methods are summarized and some of future research directions are discussed. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： bayesian methods Performance assessment Diagnosis Control monitoring Process monitoring bayesian network

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bayesian methods FOR ERASURE INSERTION IN FREQUENCY-HOP COMMUNICATION-SYSTEMS WITH PARTIAL-BAND INTERFERENCE

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IEEE TRANSACTIONS ON COMMUNICATIONS 1992年第7期40卷 1231-1238页

作者： BAUM, CW PURSLEY, MB UNIV ILLINOIS DEPT ELECT & COMP ENGNURBANAIL 61801

The erasure of unreliable symbols improves the performance of most types of error-control coding if a good method is used to decide which symbols should be erased. bayesian decision theory is employed to obtain such a method for use in frequency-hop communications with Reed-Solomon coding and errors-and-erasures decoding. The performance of frequency-hop communications with bayesian erasure insertion is analyzed for channels with both partial-band and wideband Gaussian noise. The bayesian technique is compared with Viterbi's ratio-threshold test, and these are compared to receivers that do not erase and use errors-only decoding. Comparisons are also made with receivers that erase all of the symbols that are affected by the partial-band interference. When interference is strong, large coding gains result from the bayesian method, and error probabilities are reduced by several orders of magnitude.

关键词： bayesian methods Frequency Decoding Interference Decision theory Reed-Solomon codes Performance analysis Wideband Gaussian noise Viterbi algorithm

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bayesian methods for erasure insertion in frequency-hopping multiple access with rice selective fading

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2003年第6期52卷 1616-1620页

作者： De Fina, S H3G Italia SpA Technol Rome Italy

A bayesian decision rule for erasure insertion is derived in this paper, assuming frequency-hop multiple-access communications in Rician selective fading. The proposed method is based on a channel-identification approach together with decision feedback. Given the propagation environment under study, which can be deemed typical for broad-band mobile systems, the Rice factor, in addition to the channel power delay profile, need to be estimated by the receiver. Significant performance gain, compared to the simple ratio-threshold test (RTT), can be achieved with the proposed method at the expense of greater complexity, mainly due to the channel-identification requirement. Nevertheless, in this paper it is shown that this bayesian decision rule exhibits high robustness on respect to the joint estimation of the Rice factor and power-delay profile, thus proving its actual applicability in real receivers employing erasure insertion.

关键词： bayesian methods Frequency Fading Delay estimation Mobile communication Rician channels Feedback Propagation delay Performance gain Testing

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bayesian methods in Human Drug and Biological Products Development in CDER and CBER

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THERAPEUTIC INNOVATION & REGULATORY SCIENCE 2023年第3期57卷 436-444页

作者： Ionan, Alexei C. C. Clark, Jennifer Travis, James Amatya, Anup Scott, John Smith, James P. P. Chattopadhyay, Somesh Salerno, Mary Jo Rothmann, Mark US FDA Ctr Drug Evaluat & Res Off Translat Sci Off Biostat Silver Spring MD 20993 USA US FDA Div Biostat Ctr Biol Evaluat & Res Off Biostat & Pharmacovigilance Silver Spring MD USA US FDA Ctr Drug Evaluat & Res Off New Drugs Off New Drug Policy Silver Spring MD USA

The Center for Drug Evaluation and Research (CDER) and the Center for Biologics Evaluation and Research (CBER) of the U.S. Food and Drug Administration (FDA) have been leaders in protecting and promoting the U.S. public health by helping to ensure that safe and effective drugs and biological products are available in the United States for those who need them. The null hypothesis significance testing approach, along with other considerations, is typically used to demonstrate the effectiveness of a drug or biological product. The bayesian framework presents an alternative approach to demonstrate the effectiveness of a treatment. This article discusses the bayesian framework for drug and biological product development, highlights key settings in which bayesian approaches may be appropriate, and provides recent examples of the use of bayesian approaches within CDER and CBER.

关键词： FDA bayesian methods Clinical trials Adaptive design

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bayesian methods applied to the generalized matching law

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JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR 2019年第2期111卷 252-273页

作者： Villarreal, Manuel Velazquez, Carlos Baroja, Jose L. Segura, Alejandro Bouzas, Arturo Lee, Michael D. Univ Nacl Autonoma Mexico Fac Psicol Mexico City DF Mexico Univ Calif Irvine Dept Cognit Sci Irvine CA 92717 USA Univ Guadalajara Ctr Estudios & Invest Comportamiento Guadalajara Jalisco Mexico

We demonstrate the usefulness of bayesian methods in developing, evaluating, and using psychological models in the experimental analysis of behavior. We do this through a case study, involving new experimental data that measure the response count and time allocation behavior in pigeons under concurrent random-ratio random-interval schedules of reinforcement. To analyze these data, we implement a series of behavioral models, based on the generalized matching law, as graphical models, and use computational methods to perform fully bayesian inference. We demonstrate how bayesian methods, implemented in this way, make inferences about parameters representing psychological variables, how they test the descriptive adequacy of models as accounts of behavior, and how they compare multiple competing models. We also demonstrate how the bayesian graphical modeling approach allows for more complicated modeling structures, including hierarchical, common cause, and latent mixture structures, to formalize more complicated behavioral models. As part of the case study, we demonstrate how the statistical properties of bayesian methods allow them to provide more direct and intuitive tests of theories and hypotheses, and how they support the creative and exploratory development of new theories and models.

关键词： bayesian methods graphical models generalized matching law concurrent schedules

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bayesian methods for early detection of changes in childhood cancer incidence: Trends for acute lymphoblastic leukaemia are consistent with an infectious aetiology

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EUROPEAN JOURNAL OF CANCER 2006年第1期42卷 78-83页

作者： Maule, MM Zuccolo, L Magnani, C Pastore, G Dalmasso, P Pearce, N Merletti, F Gregori, D S Giovanni Hosp CPO Piemonte CeRMS Canc Epidemiol UnitChildhood Canc Registry Piedm Turin Italy Univ Turin Dept Publ Hlth & Microbiol Med Stat Unit I-10124 Turin Italy Univ Piemonte Orientale Dept Med Sci Unit Med Stat & Epidemiol Novara Italy Univ Piemonte Orientale Dept Med Sci Div Paediat Novara Italy Massey Univ Ctr Publ Hlth Res Wellington New Zealand

Published data on time trends in the incidence of childhood leukaemia show inconsistent patterns, with some studies showing increases and others showing relatively stable incidence rates. Data on time trends in childhood cancer incidence from the Childhood Cancer Registry of Piedmont, Italy were analysed using two different approaches: standard Poisson regression and a bayesian regression approach including an autoregressive component. Our focus was on acute lymphoblastic leukaemia (ALL), since this is hypothesised to have an infectious aetiology, but for purposes of comparison we also conducted similar analyses for selected other childhood cancer sites (acute non-lymphoblastic leukaemia (AnLL), central nervous system (CNS) tumours and neuroblastoma (NB)). The two models fitted the data equally well, but led to different interpretations of the time trends. The first produced ever-increasing rates, while the latter produced non-monotonic patterns, particularly for ALL, which showed evidence of a cyclical pattern. The bayesian analysis produced findings that are consistent with the hypothesis of an infectious aetiology for ALL, but not for AnLL or for solid tumours (CNS and NB). Although sudden changes in time trends should be interpreted with caution, the results of the bayesian approach are consistent with current knowledge of the natural history of childhood ALL, including a short latency time and the postulated infectious aetiology of the disease. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： childhood leukaemia incidence trend bayesian methods

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bayesian methods for uncertainty factor application for derivation of reference values

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REGULATORY TOXICOLOGY AND PHARMACOLOGY 2016年 80卷 9-24页

作者： Simon, Ted W. Zhu, Yiliang Dourson, Michael L. Beck, Nancy B. Ted Simon LLC 4184 Johnston Rd Winston GA 30187 USA Univ S Florida Dept Epidemiol & Biostat 13201 Bruce B DownsMDC56 Tampa FL 33612 USA Univ Cincinnati TERA Ctr Coll Med 160 Panzeca Way Cincinnati OH 45267 USA Amer Chem Council Regulatory Sci Policy Regulatory & Tech Affairs 700 2nd St NE Washington DC 20002 USA

In 2014, the National Research Council (NRC) published Review of EPA's Integrated Risk Information System (IRIS) Process that considers methods EPA uses for developing toxicity criteria for non-carcinogens. These criteria are the Reference Dose (RfD) for oral exposure and Reference Concentration (RfC) for inhalation exposure. The NRC Review suggested using bayesian methods for application of uncertainty factors (UFs) to adjust the point of departure dose or concentration to a level considered to be without adverse effects for the human population. The NRC foresaw bayesian methods would be potentially useful for combining toxicity data from disparate sources high throughput assays, animal testing, and observational epidemiology. UFs represent five distinct areas for which both adjustment and consideration of uncertainty may be needed. NRC suggested UFs could be represented as bayesian prior distributions, illustrated the use of a log-normal distribution to represent the composite UF, and combined this distribution with a log-normal distribution representing uncertainty in the point of departure (POD) to reflect the overall uncertainty. Here, we explore these suggestions and present a refinement of the methodology suggested by NRC that considers each individual UF as a distribution. From an examination of 24 evaluations from EPA's IRIS program, when individual UFs were represented using this approach, the geometric mean fold change in the value of the RfD or RfC increased from 3 to over 30, depending on the number of individual UFs used and the sophistication of the assessment. We present example calculations and recommendations for implementing the refined NRC methodology. (C) 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license.

关键词： Uncertainty factor bayesian methods Reference dose Reference concentration Risk assessment Hazard assessment

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