Power of Probability in Psychometrics. Review of the book “Bayesian Psychometric Modeling“
Вопросы образования, 2023 The emergence and development of Bayesian psychometrics is a result of psychometrics' desire to reduce measurement error. This book is the first to present a systematic description of the Bayesian approach in psychometric research.
Ирина Угланова
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Learning Summary Statistics for Bayesian Inference with Autoencoders
SciPost Physics Core, 2022 For stochastic models with intractable likelihood functions, approximate Bayesian computation offers a way of approximating the true posterior through repeated comparisons of observations with simulated model outputs in terms of a small set of summary
Carlo Albert, Simone Ulzega, Firat Ozdemir, Fernando Perez-Cruz, Antonietta Mira
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Estimation Of Parameters And Selection Of Models Applied To Population Balance Dynamics Via Approximate Bayesian Computational [PDF]
Journal of Heat and Mass Transfer Research, 2022 Population balance models mathematically describe the particle size distribution based on modeling physical phenomena that influence the distribution, such as aggregation, growth, and breakage.
Carlos Moura +4 more
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Change-point model on nonhomogeneous Poisson processes with application in copy number profiling by next-generation DNA sequencing [PDF]
, 2012 We propose a flexible change-point model for inhomogeneous Poisson Processes, which arise naturally from next-generation DNA sequencing, and derive score and generalized likelihood statistics for shifts in intensity functions.
Shen, Jeremy J., Zhang, Nancy R.
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Philosophy and the practice of Bayesian statistics [PDF]
, 2010 A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics.
Abbott +138 more
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Why Bayesian Ideas Should Be Introduced in the Statistics Curricula and How to Do So
Journal of Statistics Education, 2020 While computing has become an important part of the statistics field, course offerings are still influenced by a legacy of mathematically centric thinking.
Andrew Hoegh
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A Bayesian Statistics Course for Undergraduates: Bayesian Thinking, Computing, and Research
Journal of Statistics Education, 2020 We propose a semester-long Bayesian statistics course for undergraduate students with calculus and probability background. We cultivate students’ Bayesian thinking with Bayesian methods applied to real data problems. We leverage modern Bayesian computing
Jingchen Hu
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Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem [PDF]
, 2010 This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish ...
Berger, James O., Scott, James G.
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A Web Simulator to Assist in the Teaching of Bayes’ Theorem
Journal of Statistics Education, 2019 Teaching some concepts in statistics greatly benefits from individual practice with immediate feedback. In order to provide such practice to a large number of students we have written a simulator based on an historical event: the loss in May 22, 1968 ...
M. J. Bárcena +4 more
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The Astrophysical Journal Supplement Series, 2023 Radio interferometers designed to probe the 21 cm signal from Cosmic Dawn and the Epoch of Reionization must contend with systematic effects that make it difficult to achieve sufficient dynamic range to separate the 21 cm signal from foreground emission ...
Fraser Kennedy +4 more
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