Results 1 to 10 of about 294,457 (253)

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, Mohammad K, Zeraati H, Ramezani Tehrani F, Mansournia MA.   +4 more
europepmc   +4 more sources

Approximate Bayesian computational methods [PDF]

Statistics and Computing, 2011
7 ...
Christian Robert, Jean-Michel Marin, Robin Ryder   +2 more
exaly   +5 more sources

A Tutorial on Modern Bayesian Methods in Clinical Trials. [PDF]

Ther Innov Regul Sci, 2023
Muehlemann N, Zhou T, Mukherjee R, Hossain MI, Roychoudhury S, Russek-Cohen E.   +5 more
europepmc   +2 more sources

Abnormality Detection and Failure Prediction Using Explainable Bayesian Deep Learning: Methodology and Case Study with Industrial Data

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, Srinivasa Rao Pedapati, Masdi Muhammad, Víctor Leiva   +3 more
doaj   +1 more source

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, Gregoire Guillet, Tobias Bolch, Tobias Bolch   +3 more
doaj   +1 more source

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, Tomohiro Ohigashi, Kengo Nagashima, Yuri Ito, Kazushi Maruo   +4 more
doaj   +1 more source

p-value based statistical significance tests: Concepts, misuses, critiques, solutions and beyond [PDF]

Computational Ecology and Software, 2022
The p-value is at the heart of statistical significance tests, a very important issue related to the role of statistical inference in advancing scientific discovery. Over the past few decades, p-value based statistical significance tests have been widely
WenJun Zhang
doaj  

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, John Newell, John Hinde   +2 more
doaj   +1 more source

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
doaj   +1 more source

The Role of Digital Media in Shaping Youth Planetary Health Interests in the Global Economy

Journal of Open Innovation: Technology, Market and Complexity, 2020
Despite revolutionizing the work of practicing economists by providing a direct link between neo-classical economic theory and revealed market preference data, Random Utility Theory has yet to guide research applications in global market sustainability ...
Ibrahim Niankara, Muhammad Noor Al adwan, Aminata Niankara   +2 more
doaj   +1 more source