Results 11 to 20 of about 371,316 (301)
Bayesian methods for clinicians. [PDF]
Med J Islam Repub Iran, 2020 Background: The Bayesian methods have received more attention in medical research. It is considered as a natural paradigm for dealing with applied problems in the sciences and also an alternative to the traditional frequentist approach. However, its concept is somewhat difficult to grasp by nonexperts. This study aimed to explain the foundational ideas
Bidhendi Yarandi R +4 more
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Bayesian Computational Methods [PDF]
, 2011 In this chapter, we will first present the most standard computational challenges met in Bayesian Statistics, focussing primarily on mixture estimation and on model choice issues, and then relate these problems with computational solutions. Of course, this chapter is only a terse introduction to the problems and solutions related to Bayesian ...
Robert, Christian P.
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Approximate Bayesian computational methods [PDF]
Statistics and Computing, 2011 7 ...
Jean-Michel Marin +2 more
exaly +5 more sources
A Tutorial on Modern Bayesian Methods in Clinical Trials. [PDF]
Ther Innov Regul Sci, 2023 Muehlemann N +5 more
europepmc +2 more sources
SSRN Electronic Journal, 2011 Chapter written for the Handbook of Research Methods and Applications on Empirical Macroeconomics, edited by Nigar Hashimzade and Michael Thornton, forth- coming in 2012 (Edward Elgar Publishing). This chapter presents an introductory review of Bayesian methods for research in empirical macroeconomics.
Bauwens, L, Korobilis, D
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Mathematics, 2022 Mistrust, amplified by numerous artificial intelligence (AI) related incidents, is an issue that has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods.
Ahmad Kamal Mohd Nor +3 more
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Bayesian estimation of glacier surface elevation changes from DEMs
Frontiers in Earth Science, 2023 Accurate estimates of glacier surface elevation changes are paramount for various aspects of the study of the cryosphere, from glacier flow and thickness estimates to hydrological forecasts and projections of sea-level-rise.
Gregoire Guillet +3 more
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Bias in Odds Ratios From Logistic Regression Methods With Sparse Data Sets
Journal of Epidemiology, 2023 Background: Logistic regression models are widely used to evaluate the association between a binary outcome and a set of covariates. However, when there are few study participants at the outcome and covariate levels, the models lead to bias of the odds ...
Masahiko Gosho +4 more
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Jump test and Estimate the Size and Probability of Jump in the Stock Market Using Stochastic Volatility Models [PDF]
مدلسازی اقتصادسنجی, 2022 New findings show that volatility models with jump component are more successful than without jumping models in modeling stylized facts about the stock market.
Alireza Najjarpour, Mojtaba Rostami
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A Bayesian Approach for Imputation of Censored Survival Data
Stats, 2022 A common feature of much survival data is censoring due to incompletely observed lifetimes. Survival analysis methods and models have been designed to take account of this and provide appropriate relevant summaries, such as the Kaplan–Meier plot and the ...
Shirin Moghaddam +2 more
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