Results 41 to 50 of about 24,269,673 (319)
Journal of the American Medical Association (JAMA), 2018 Importance Bayesian analysis of clinical trial data may provide useful information to aid in study interpretation, especially when trial evidence suggests that the benefits of an intervention are uncertain, such as in a trial that evaluated early ...
E. Goligher +8 more
semanticscholar +1 more source
Theory and practice of Bayesian and frequentist frameworks for network meta-analysis
BMJ evidence-based medicine, 2022 Network meta-analysis (NMA) is an increasingly popular statistical method of synthesising evidence to assess the comparative benefits and harms of multiple treatments in a single analysis.
B. Sadeghirad +6 more
semanticscholar +1 more source
Plant Production Science, 2019 Crop phenotyping is a key process used to accelerate breeding programs in the era of high-throughput genotyping. However, most rapid phenotyping methods developed to date have focused on major cereals or legumes, and their application to minor crops has ...
Kohtaro Iseki, Ryo Matsumoto
doaj +1 more source
Bayesian adaptive lasso quantile regression [PDF]
, 2012 Recently, variable selection by penalized likelihood has attracted much research interest. In this paper, we propose adaptive Lasso quantile regression (BALQR) from a Bayesian perspective.
Al-Hamzawi, Rahim +2 more
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İktisat Politikası Araştırmaları Dergisi, 2023 In this paper, the authors explored the interaction of macroeconomic variables with some form of vague interrelationships. The relevance of factor analysis has demonstrated an existing association between manifest and latent variables in helping the ...
Christopher E. S. Warburton +1 more
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Comment on Article by Ferreira and Gamerman
, 2015 Comment on Article by Ferreira and Gamerman [arXiv:1509.03410].Comment: Published at http://dx.doi.org/10.1214/15-BA944C in the Bayesian Analysis (http://projecteuclid.org/euclid.ba) by the International Society of Bayesian Analysis (http://bayesian ...
Zidek, James V.
core +1 more source
Bayesian inference with information content model check for Langevin equations [PDF]
, 2017 The Bayesian data analysis framework has been proven to be a systematic and effective method of parameter inference and model selection for stochastic processes.
Krog, Jens, Lomholt, Michael A.
core +2 more sources
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model [PDF]
arXiv.org, 2015 We aim to produce predictive models that are not only accurate, but are also interpretable to human experts. Our models are decision lists, which consist of a series of if...then... statements (e.g., if high blood pressure, then stroke) that discretize a
Benjamin Letham +3 more
semanticscholar +1 more source
Structural reliability analysis: A Bayesian perspective
Structural Safety, 2022 10 Numerical methods play a dominant role in structural reliability analysis, and the goal has long been 11 to produce a failure probability estimate with a desired level of accuracy using a minimum number of 12 performance function evaluations.
C. Dang +4 more
semanticscholar +1 more source
Bayesian Analysis of Complex Mutations in HBV, HCV, and HIV Studies
Big Data Mining and Analytics, 2019 In this article, we aim to provide a thorough review of the Bayesian-inference-based methods applied to Hepatitis B Virus (HBV), Hepatitis C Virus (HCV), and Human Immunodeficiency Virus (HIV) studies with a focus on the detection of the viral mutations ...
Bing Liu +3 more
doaj +1 more source