Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...
2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China Objective To demonstrate an application of Bayesian model averaging (BMA) with generalised additive ...
This tutorial component includes defining priors based on literature and performing a sensitivity analysis to test for potential misspecification or bias. For readers new to Bayesian statistics, the ...
Thanks to their rapid evolution, viral genomes can be analyzed and compared to estimate the dispersal history of the virus responsible for an epidemic, a task known as phylogeographic inference. In ...
Orthogonal Frequency Division Multiplexing,Time Slot,Base Station,Optimization Problem,Wireless Networks,Additive Noise,Channel Estimation,Communication Systems,User Equipment,Multiple-input ...
Overall, 71.4% of studies reported non-significant primary outcomes, with an increasing trend observed over time. Conclusion: Bayesian analysis offers a useful framework for interpreting "negative ...
The project automatically fetches the latest papers from arXiv based on keywords. The subheadings in the README file represent the search keywords. Only the most recent articles for each keyword are ...
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