Results 21 to 30 of about 1,294,144 (288)
Decision algorithms and flow graphs; a rough set approach
Journal of Telecommunications and Information Technology, 2003 This paper concerns some relationship between Bayes` theorem and rough sets. It is revealed that any decision algorithm satisfies Bayes` theorem, without referring to either prior or posterior probabilities inherently associated with classical Bayesian ...
Zdzisław Pawlak
doaj +1 more source
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.
core +2 more sources
Kolmogorov's axioms for probabilities with values in hyperbolic numbers [PDF]
, 2015 We introduce the notion of a probabilistic measure which takes values in hyperbolic numbers and which satisfies the system of axioms generalizing directly Kolmogorov's system of axioms.
Alpay, Daniel +2 more
core +3 more sources
Trends in epidemiology in the 21st century: time to adopt Bayesian methods
Cadernos de Saúde Pública, 2014 2013 marked the 250th anniversary of the presentation of Bayes’ theorem by the philosopher Richard Price. Thomas Bayes was a figure little known in his own time, but in the 20th century the theorem that bears his name became widely used in many fields of
Edson Zangiacomi Martinez +1 more
doaj +1 more source
Wireless Body Area Network (WBAN)-Based Telemedicine for Emergency Care
Sensors, 2020 This paper is a collection of telemedicine techniques used by wireless body area networks (WBANs) for emergency conditions. Furthermore, Bayes’ theorem is proposed for predicting emergency conditions.
Latha R, Vetrivelan P
doaj +1 more source
Constraining transfer cross sections using Bayes' theorem [PDF]
Physical Review C, 2018 Being able to rigorously quantify the uncertainties in reaction models is crucial to moving this field forward. Even though Bayesian methods are becoming increasingly popular in nuclear theory, they are yet to be implemented and applied in reaction ...
A. Lovell, F. Nunes
semanticscholar +1 more source
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua +4 more
wiley +1 more source
COVID-19 and Quantitative Literacy: Focusing on Probability
Numeracy, 2020 The COVID-19 pandemic is arguably the worst crisis the world has faced, so far, in this new century. We haven’t seen a pandemic like this since the 1918 Flu at the beginning of the last century, and, as of this writing, there appears to be no end in ...
Michael Lewis
doaj +1 more source
BMC Pregnancy and Childbirth, 2022 Background Despite international clinical guideline recommendations, implementation of Bayes-theorem based preeclampsia risk prediction model in first trimester among Chinese women is limited. The aim of this study is to examine the effectiveness of this
Qiongjie Zhou +3 more
doaj +1 more source
Statistical Information and Uncertainty: A Critique of Applications in Experimental Psychology
Entropy, 2010 This paper presents, first, a formal exploration of the relationships between information (statistically defined), statistical hypothesis testing, the use of hypothesis testing in reverse as an investigative tool, channel capacity in a communication ...
Donald Laming
doaj +1 more source