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Bayesian Scan Statistics
In this chapter we describe Bayesian scan statistics, a class of methods which build both on the prior literature on scan statistics and on Bayesian...
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Bayesian Statistics
The use of Bayesian statistical analysis is becoming more popular in the medical literature. Many clinicians will not be familiar with the Bayesian...
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Bayesian Statistics for Medical Devices: Progress Since 2010
The use of Bayesian statistics to support regulatory evaluation of medical devices began in the late 1990s. We review the literature, focusing on...
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Bayesian Statistics
Bayesian Statistics, a technique that has become very popular for many types of machine learning, starts out with a new view at statistical data: it...
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Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review
Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the...
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AI-Powered Bayesian Statistics in Biomedicine
Statistics and artificial intelligence (AI) are distinct yet closely interconnected disciplines, each characterized by its own historical roots and...
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Bayesian Statistics, New Generations New Approaches BAYSM 2022, Montréal, Canada, June 22–23
This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montréal, Canada, held on June 22–23, titled "Bayesian...
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Recent advances in algebraic geometry and Bayesian statistics
This article is a review of theoretical advances in the research field of algebraic geometry and Bayesian statistics in the last two decades. Many...
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The Development of Bayesian Statistics
The incorporation of Bayesian inference into practical statistics has seen many changes over the past century, including hierarchical and...
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Bayesian Statistics
In this book we have introduced both the practice of analyzing data using R, and covered probability theory, including estimation and testing. For...
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Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation
This paper presents a novel approach to analyzing uncertainty in complex groundwater models based on the approximate Bayesian computation (ABC)...
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Why are There not More Bayesian Clinical Trials? Ability to Interpret Bayesian and Conventional Statistics Among Medical Researchers
Objective and BackgroundWe assessed current understandings in interpretation of Bayesian and traditional statistical results within the clinical...
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Nonparametric Bayesian Inference Contributions by Jean-Marie Rolin
This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation....
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Using a Bayesian approach to reconstruct graph statistics after edge sampling
Often, due to prohibitively large size or to limits to data collecting APIs, it is not possible to work with a complete network dataset and sampling...
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New Frontiers in Bayesian Statistics BAYSM 2021, Online, September 1–3
This book presents a selection of peer-reviewed contributions to the fifth Bayesian Young Statisticians Meeting, BaYSM 2021, held virtually due to...
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Bayesian statistics in anesthesia practice: a tutorial for anesthesiologists
This narrative review intends to provide the anesthesiologist with the basic knowledge of the Bayesian concepts and should be considered as a...
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Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors
A key ingredient in approximate Bayesian computation (ABC) procedures is the choice of a discrepancy that describes how different the simulated and...
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Incorporating uncertainty in Indigenous sea Country monitoring with Bayesian statistics: Towards more informed decision-making
Partnerships in marine monitoring combining Traditional Ecological Knowledge and western science are develo** globally to improve our understanding...
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Bayesian analysis of plant DNA size distribution via non-additive statistics
We report an analysis of Cucurbitaceae DNA species through a non-additive statistics formalism. Such formalisms encompass power-law correlations. Our...
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Allometric models to estimate the individual leaf area of arabica coffee: an approach from frequentist and Bayesian statistics
Over the years, advances in technological and computational procedures have been made available for studies on plant morphology and physiology, and...
