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Undergraduate Topics in Computer Science, 2022
Maurits Kaptein, Edwin van den Heuvel
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Maurits Kaptein, Edwin van den Heuvel
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The Development of Bayesian Statistics
Journal of the Indian Institute of Science, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bayesian statistics for parasitologists
Trends in Parasitology, 2004Bayesian statistical methods are increasingly being used in the analysis of parasitological data. Here, the basis of differences between the Bayesian method and the classical or frequentist approach to statistical inference is explained. This is illustrated with practical implications of Bayesian analyses using prevalence estimation of strongyloidiasis
María-Gloria, Basáñez +4 more
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Using Bayesian statistics to detect trends in Alaskan precipitation
International Journal of Climatology, 2020Air temperature has exhibited a clear positive trend over the past several decades throughout the arctic, including Alaska. Other variables, such as precipitation, have much more uncertain trends due to inhomogeneities in measurement and high internal ...
James White, J. Walsh, R. Thoman
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Overview of Bayesian Statistics
Evaluation Review, 2020Bayesian statistics is becoming a popular approach to handling complex statistical modeling. This special issue of Evaluation Review features several Bayesian contributions. In this overview, I present the basics of Bayesian inference. Bayesian statistics is based on the principle that parameters have a distribution of beliefs about them that behave ...
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An introduction to Bayesian statistics in health psychology
Health Psychology Review, 2017 Sarah Depaoli +2 more
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Signal Processing, 2020
An improved adaptive variational Bayesian cubature information fusion algorithm for nonlinear multi-sensor systems with uncertain noise statistics is proposed in this paper.
Xiangxiang Dong, L. Chisci, Yunze Cai
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An improved adaptive variational Bayesian cubature information fusion algorithm for nonlinear multi-sensor systems with uncertain noise statistics is proposed in this paper.
Xiangxiang Dong, L. Chisci, Yunze Cai
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Understanding Bayesian Statistics
Journal of Spinal Disorders & Techniques, 2015Modern computing power has given us the ability to approach statistical questions in a manner which was previously impossible because of the time-consuming nature of the calculations required. Computer power has enabled the use of Bayesian inference techniques, based on 18th century theory, to frame statistical questions in probability.
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