Approximate Bayesian Computational methods
Statistics and Computing, 2011 Also known as likelihood-free methods, approximate Bayesian computational (ABC) methods have appeared in the past ten years as the most satisfactory approach to untractable likelihood problems, first in genetics then in a broader spectrum of applications.
Marin, Jean-Michel +3 more
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A system for determining maximum tolerated dose in clinical trial
Statistical Theory and Related Fields, 2021 Toxicity study, especially in determining the maximum tolerated dose (MTD) in phase I clinical trial, is an important step in developing new life-saving drugs.
Keying Ye +3 more
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Consciously Uncertain: A Bayesian Analysis of Preferences Formation
Games, 2022 We investigate experimentally whether players deliberately use irrelevant market cues to shape their evaluations of a traded item. We implement a repeated Vickrey median price selling auction of an unusual bad where players are informed on the market ...
Marco Stimolo +3 more
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Beyond ‘significance’: principles and practice of the Analysis of Credibility [PDF]
Royal Society Open Science, 2018 The inferential inadequacies of statistical significance testing are now widely recognized. There is, however, no consensus on how to move research into a ‘post p
Robert A. J. Matthews
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Modeling Crude Oil Price Dynamics: Investigation of Jump and Volatility Using Stochastic Volatility Models (Case study: WTI crude oil prices in 2020 and 2021) [PDF]
Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān, 2020 Due to the strategic role of volatility and instability of crude oil prices and their effects on all countries of the world, different methods of modeling and forecasting are necessary.
mojtaba rostami +1 more
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Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools
Sensors, 2019 A new software package, ISEtools, is introduced for use within the popular open-source programming language R that allows Bayesian statistical data analysis techniques to be implemented in a straightforward manner.
Peter W. Dillingham +3 more
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A Bayesian Method for Characterizing Population Heterogeneity
Games, 2019 A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity.
Dale O. Stahl
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Designing cost-sharing methods for Bayesian games [PDF]
, 2016 We study the design of cost-sharing protocols for two fundamental resource allocation problems, the Set Cover and the Steiner Tree Problem, under environments of incomplete information (Bayesian model).
AS Kelso +23 more
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Model selection for the extraction of movement primitives
Frontiers in Computational Neuroscience, 2013 A wide range of blind source separation methods have been used in motor control research for the extraction of movement primitives from EMG and kinematic data.
Dominik M Endres +2 more
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Interregional Effects of Innovations in Russia: Analysis from the Bayesian Perspective [PDF]
Prostranstvennaâ ÈkonomikaThis study analyzes the interregional effects of innovation in Russia. The hypothesis of the presence of interregional effects is tested by combining the methods of spatial econometrics and Bayesian approach.
Dmitrii Sergeevich Tereshchenko
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