Results 11 to 20 of about 2,248,018 (313)
Improving Bayesian statistics understanding in the age of Big Data with the bayesvl R package [PDF]
Softw. Impacts, 2020 The exponential growth of social data both in volume and complexity has increasingly exposed many of the shortcomings of the conventional frequentist approach to statistics.
Ho, Manh-Toan +5 more
core +2 more sources
Cosmological Parameter Inference with Bayesian Statistics [PDF]
Universe, 2021 Bayesian statistics and Markov Chain Monte Carlo (MCMC) algorithms have found their place in the field of Cosmology. They have become important mathematical and numerical tools, especially in parameter estimation and model comparison.
Luis E. Padilla +3 more
doaj +2 more sources
Introduction to Quantitative Ecology, 2021 Abstract The chapter “Bayesian Statistics” gives a brief overview of the Bayesian approach to statistical analysis. It starts off by examining the difference between frequentist statistics and Bayesian statistics. Next, it introduces Bayes’ theorem and explains how the theorem is used in statistics and model selection, with the ...
Göran Kauermann +2 more
semanticscholar +3 more sources
Bayesian Statistics for Medical Devices: Progress Since 2010. [PDF]
Ther Innov Regul Sci, 2023 The use of Bayesian statistics to support regulatory evaluation of medical devices began in the late 1990s. We review the literature, focusing on recent developments of Bayesian methods, including hierarchical modeling of studies and subgroups, borrowing
Campbell G +3 more
europepmc +2 more sources
Challenges and Opportunities for Bayesian Statistics in Proteomics. [PDF]
J Proteome Res, 2022 Proteomics is a data-rich science with complex experimental designs and an intricate measurement process. To obtain insights from the large data sets produced, statistical methods, including machine learning, are routinely applied.
Crook OM, Chung CW, Deane CM.
europepmc +2 more sources
Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics. [PDF]
Philos Trans A Math Phys Eng Sci, 2023 Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists.
Bon JJ +14 more
europepmc +3 more sources
JAMA Netw Open, 2023 Key Points Question What role could bayesian statistics play in data analysis for trauma-related clinical trials? Findings In this quality improvement study with a post hoc bayesian analysis of the Pragmatic Randomized Optimal Platelet and Plasma Ratios ...
Lammers D +3 more
europepmc +2 more sources
Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review. [PDF]
BMC Med Res MethodolBayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatments, interventions, and medical procedures. The Bayesian framework offers
Lee SY.
europepmc +2 more sources
The Importance of Prior Sensitivity Analysis in Bayesian Statistics: Demonstrations Using an Interactive Shiny App. [PDF]
Front Psychol, 2020 The current paper highlights a new, interactive Shiny App that can be used to aid in understanding and teaching the important task of conducting a prior sensitivity analysis when implementing Bayesian estimation methods.
Depaoli S, Winter SD, Visser M.
europepmc +2 more sources
Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics [PDF]
PLoS Genetics, 2013 Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid ...
C. Giambartolomei +6 more
semanticscholar +1 more source