Showing 41 - 60 results of 66 for search '"Bayesian model"', query time: 0.09s Refine Results
  1. 41

    Intelligent model for forecasting fluctuations in the gold price by Mahdieh Tavassoli, Mahnaz Rabeei, Kiamars Fathi Hafshejani

    Published 2024-09-01
    “…It is the first Iranian research in which the fluctuations in this market are modeled using non-linear Bayesian Model Averaging (BMA) and deep neural network approaches.Methodology: It is applied research where monthly data collected from 2010 to 2022 were used. …”
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  2. 42

    Assessing the dynamics of  Mycobacterium bovis infection in three French badger populations by Calenge, Clément, Payne, Ariane, Réveillaud, Édouard, Richomme, Céline, Girard, Sébastien, Desvaux, Stéphanie

    Published 2024-01-01
    “…Our first aim was to describe the dynamics of the infection in these clusters. We developed a Bayesian model of prevalence accounting for the spatial structure of the cases, the imperfect and variable sensitivity of the diagnostic tests, and the correlation of the infection status of badgers in the same commune caused by local factors (e.g., social structure and proximity to infected farms). …”
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  3. 43

    Genetic structure of the collection of ryegrass (<i>Lolium</i>) cultivars: a study based on SSR and SCoT markers by Yu. M. Mavlyutov, E. A. Vertikova, A. O. Shamustakimova, I. A. Klimenko

    Published 2023-10-01
    “…Genetic relationships among the studied cultivars were analyzed on the basis of the Neighbor-Joining dendrogram and Bayesian model.Results. To assess the genetic polymorphism of ryegrass species and varieties, 7 SSR loci were selected, for which 110 allelic variants were identified (34 alleles were unique for individual cultivars), and 9 SCoT loci, for which 78 polymorphic amplification fragments were identified, with 28 being cultivar-specific. …”
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  4. 44

    Advanced Machine Learning Ensembles for Improved Precipitation Forecasting: The Modified Stacking Ensemble Strategy in China by Tiantian Tang, Yifan Wu, Yujie Li, Lexi Xu, Xinyi Shi, Haitao Zhao, Guan Gui

    Published 2025-01-01
    “…The MSES was then evaluated against the traditional Bayesian model averaging (BMA) approach. Our comprehensive evaluation, based on deterministic forecasting metrics such as the anomaly correlation coefficient (ACC), mean squared skill score (MSSS), and Graded Precipitation Score (Pg), demonstrated the MSES outperformed individual models and the BMA method. …”
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  5. 45

    Geospatial mapping of drug-resistant tuberculosis prevalence in Africa at national and sub-national levels by Alemneh Mekuriaw Liyew, Archie C.A. Clements, Fasil Wagnew, Beth Gilmour, Kefyalew Addis Alene

    Published 2025-04-01
    “…Methods: We assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels. …”
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  6. 46

    Downscaling and Projection of Multi-CMIP5 Precipitation Using Machine Learning Methods in the Upper Han River Basin by Ren Xu, Nengcheng Chen, Yumin Chen, Zeqiang Chen

    Published 2020-01-01
    “…This study developed multiple machine learning (ML) downscaling models, based on a Bayesian model average (BMA), to downscale the precipitation simulation of 8 Coupled Model Intercomparison Project Phase 5 (CMIP5) models using model output statistics (MOS) for the years 1961–2005 in the upper Han River basin. …”
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  7. 47

    Value of Plasma NGAL and Creatinine on First Day of Admission in the Diagnosis of Cardiorenal Syndrome Type 1 by Hao Phan Thai, Bao Hoang Bui, Tien Hoang Anh, Minh Huynh Van

    Published 2020-01-01
    “…Building the optimal regression model (without eGFRCKDEPID1) by the BMA (Bayesian model average) method with two variables NGAL and Creatinine D1, we had the equation: odds ratio = ey while y = −2.39 + 0.0037 × NGAL + 0.17 × Creatinine D1. …”
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  8. 48

    The dynamics of sea otter prey selection under population growth and expansion by Clinton B. Leach, Benjamin P. Weitzman, James L. Bodkin, Daniel Esler, George G. Esslinger, Kimberly A. Kloecker, Daniel H. Monson, Jamie N. Womble, Mevin B. Hooten

    Published 2024-12-01
    “…Specifically, we developed a multilevel Bayesian model to capture how sea otter diet at a location (the number, type, and size of prey collected) changed as a function of local cumulative otter abundance and the year in which the location was first occupied. …”
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  9. 49

    Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field by Zhikai Yu, Binghao Yang, Penghu Wei, Hang Xu, Yongzhi Shan, Xiaotong Fan, Huaqiang Zhang, Changming Wang, Jingjing Wang, Shan Yu, Guoguang Zhao

    Published 2025-01-01
    “…The Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models, whereas the Naive Bayesian model necessitates the least amount of computational and storage space. …”
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  10. 50

    A novel model-based meta-analysis to indirectly estimate the comparative efficacy of two medications: an example using DPP-4 inhibitors, sitagliptin and linagliptin, in treatment o... by Yan Gong, James Rogers, Christian Friedrich, Sanjay Patel, Alexander Staab, Jorge Luiz Gross, Daniel Polhamus, William Gillespie, Brigitta Ursula Monz, Silke Retlich

    Published 2013-03-01
    “…Comparison of two oral dipeptidyl peptidase (DPP)-4 inhibitors, sitagliptin and linagliptin, for type 2 diabetes mellitus (T2DM) treatment was used as an example.Design Systematic review with MBMA.Data sources MEDLINE, EMBASE, http://www.ClinicalTrials.gov, Cochrane review of DPP-4 inhibitors for T2DM, sitagliptin trials on Food and Drug Administration website to December 2011 and linagliptin data from the manufacturer.Eligibility criteria for selecting studies Double-blind, randomised controlled clinical trials, ≥12 weeks’ duration, that analysed sitagliptin or linagliptin efficacies as changes in glycated haemoglobin (HbA1c) levels, in adults with T2DM and HbA1c &gt;7%, irrespective of background medication.Model development and application A Bayesian model was fitted (Markov Chain Monte Carlo method). …”
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  11. 51

    Remote-sensing-based forest canopy height mapping: some models are useful, but might they provide us with even more insights when combined? by N. Besic, N. Picard, C. Vega, J.-D. Bontemps, L. Hertzog, J.-P. Renaud, J.-P. Renaud, F. Fogel, M. Schwartz, A. Pellissier-Tanon, G. Destouet, F. Mortier, F. Mortier, M. Planells-Rodriguez, P. Ciais

    Published 2025-01-01
    “…This article seeks to endorse the latter by utilizing the Bayesian model averaging approach to diagnose and interpret the differences between predictions from different models. …”
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  12. 52

    PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy by Lovro Palaversa, Željko Ivezić, Neven Caplar, Karlo Mrakovčić, Bob Abel, Oleksandra Razim, Filip Matković, Connor Yablonski, Toni Šarić, Tomislav Jurkić, Sandro Campos, Melissa DeLucchi, Derek Jones, Konstantin Malanchev, Alex I. Malz, Sean McGuire, Mario Jurić

    Published 2025-01-01
    “…Anticipating photometric catalogs with tens of billions of stars from Rubin's Legacy Survey of Space and Time (LSST), we present a Bayesian model and pipeline that build on previous work and can handle LSST-sized datasets. …”
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  13. 53

    I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations by Carolyn S Calfee, Michael A Matthay, Paul Henderson, Martin Eklund, Laura J Esserman, Chirag Patel, Angela Haczku, Michelle Jung, Tony Oliver, Alessio Crippa, Andrea Discacciati, Kathleen D Liu, Ellen L Burnham, Nuala J Meyer, Fady A Youssef, Derek W Russell, Julie Lang, Kevin W Gibbs, Daniel C Files, Sheetal Gandotra, Purnema Madahar, Nathan K Cobb, Timothy E Albertson, Rajiv Sonti, John P Reilly, Alejandra Jauregui, Iván García, Luis E Huerta, Daniel Clark Files, Neil R Aggarwal, Adam L Asare, Jeremy R Beitler, Paul A Berger, George Cimino, Melissa H Coleman, Paul T Henderson, Caroline A G Ittner, Kashif T Khan, Jonathan L Koff, Mary LaRose, Joe Levitt, Ruixiao Lu, Jeffrey D McKeehan, Karl W Thomas, Aaron M Mittel, Albert F Yen, Alexis E Suarez, Alexis L Serra, Alpesh N Amin, Amanda Rosen, Amy L Dzierba, Anna D Barker, Ariel R Weisman, Brian M Daniel, Brian M Morrissey, Caroline AG Ittner, Chayse Jones, Christina Creel-Bulos, Christina M Angelucci, Diana Ng, Fredy Chaparro-Rojas, Gavin H Harris, Harsh V Barot, Heny Su, Jacqueline B Sutter, Jamal Dodin, Jerry S Lee, John Kazianis, Joshua F Detelich, Julie E Lang, Justin Muir, Katarzyna Gosek, Katherine L Nugent, Kimberly Yee, Laura G Rodrigues, Laura R Macias, Lindsey A Orr, Lindsie L Boerger, Lissette Rosario-Remigio, Lucia Kufa, Maged Tanios, Maria B Reyes, Max W Adelman, Maya M Juarez, Michelle Meyers, Mitchell P Sternlieb, Neil Aggarwal, Nilam S Mangalmurti, Patrice Jones, Paul L Saban, Peter S Marshall, Philiip A Robinson, Philip Yang, Rahul Nair, Richard Anthony Lee, Richard G Wunderink, Romina Wahab, Roxana A Lupu, Santhi I Kumar, Sara C Auld, Scott Fields, Se Fum Wong, Skyler J Pearson, Spencer Whealon, Timothy F Obermiller, Anita Darmanian, John Schicchi, Esmeralda Martinez, Farjad Sarafian, Julie Nguyen, Bethany Weiler-Lisowski, Jaime Wyatt, Daniel Blevins, Marylee Melendrez, Brenda Lopez, Hiwet Tzehaie, Omowunmi Amosu, Austin Simonson, Erin Hardy, Brett Lindgren, Gregory Peterfreund, Leigha Landreth, Lisa Parks

    Published 2022-06-01
    “…The statistical design uses a Bayesian model with ‘stopping’ and ‘graduation’ criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. …”
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  14. 54

    Frequency-specific changes in prefrontal activity associated with maladaptive belief updating in volatile environments in euthymic bipolar disorder by Marina Ivanova, Ksenia Germanova, Dmitry S. Petelin, Aynur Ragimova, Grigory Kopytin, Beatrice A. Volel, Vadim V. Nikulin, Maria Herrojo Ruiz

    Published 2025-01-01
    “…Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. …”
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  15. 55

    Genome-wide association study and genomic prediction of root system architecture traits in Sorghum (Sorghum bicolor (L.) Moench) at the seedling stage by Muluken Enyew, Mulatu Geleta, Kassahun Tesfaye, Amare Seyoum, Tileye Feyissa, Admas Alemu, Cecilia Hammenhag, Anders S. Carlsson

    Published 2025-01-01
    “…The genomic prediction accuracy estimated for the studied traits using five Bayesian models ranged from 0.30 to 0.63 while it ranged from 0.35 to 0.60 when the RR-BLUP model was used. …”
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  16. 56

    Individual differences in event experiences and psychosocial factors as drivers for perceived linguistic change following occupational major life events by Wirtz Mason A., Pickl Simon, Pfenninger Simone E.

    Published 2025-02-01
    “…We analyzed survey data from 154 German-speaking adults in Austria who experienced (at least) one of these career-related MLEs. Results from Bayesian modeling showed that individual differences in event experiences (e.g., how stressful an MLE is perceived, how damaging an MLE is for one’s social status) alongside social factors such as varietal proficiency affect the degree of perceived MLE-related change in the sociolinguistic repertoire. …”
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  17. 57

    Bayesian Estimation for the Doubly Censored Topp Leone Distribution using Approximate Methods and Fuzzy Type of Priors by Navid Feroze, Ali Al-Alwan, Muhammad Noor-ul-Amin, Shajib Ali, R. Alshenawy

    Published 2022-01-01
    “…The Fuzzy priors can be used as prior information in the Bayesian models. This paper considers the posterior analysis of TLD, when the samples are doubly censored. …”
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  18. 58

    Inference of a three-gene network underpinning epidermal stem cell development in Caenorhabditis elegans by Alicja Brożek, Arianna Ceccarelli, Andreas Christ Sølvsten Jørgensen, Mark Hintze, Vahid Shahrezaei, Michalis Barkoulas

    Published 2025-02-01
    “…We validate its significance at the L1 stage with ordinary differential equations and Bayesian modeling, making testable predictions for a double mutant. …”
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  19. 59

    Introduction risk of fire ants through container cargo in ports: Data integration approach considering a logistic network. by Shota Homma, Daisuke Murakami, Shinya Hosokawa, Koji Kanefuji

    Published 2025-01-01
    “…A relationship between locations based on logistics connectivity is assumed rather than the spatial correlation based on the geographical distance used in the past. Hierarchical Bayesian models integrating data through the network were implemented for two fire ant species (Solenopsis invicta and Solenopsis geminata) observed in Japanese ports. …”
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  20. 60

    The Heating Efficiency of Hot Jupiters from a Data-driven Perspective by Sheng Jin, Dong-Hong Wu, Yi-Xuan Cao, Zi-Yi Guo

    Published 2025-01-01
    “…By connecting planetary thermal evolution models with the observed properties of hot Jupiters using hierarchical Bayesian models, a theoretical parameter called the heating efficiency has been introduced to describe the heating of the interiors of these planets. …”
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