Results 141 to 150 of about 40,175 (220)
An Interactive Workshop Reviewing Basic Biostatistics and Applying Bayes' Theorem to Diagnostic Testing and Clinical Decision-Making. [PDF]
MedEdPORTAL, 2018 Nelson A.
europepmc +1 more source
Honorary Lecture on S. James Press and Bayesian Analysis
S. James Press's many contributions to statistical research, lecturing, mentoring students, the statistics profession, etc. are summarized. Then some new developments in Bayesian analysis are described and remarks on the future of Bayesian analysis are ...
Arnold Zellner
core
Bayes' Theorem: "Adjustment of Subjective Confidence"
, 1998 This website, created by Richard Lowry of Vassar College, is an application of Bayes' Theorem that performs the same calculations for the situation where the several probabilities are constructed as indices of subjective confidence.
Lowry, Richard
core
Mathematical Finance, Volume 36, Issue 3, Page 595-619, July 2026.ABSTRACT We introduce a dynamic and stochastic interbank model with an endogenous notion of distress contagion, arising from rational worries about future defaults and ensuing losses. This entails a mark‐to‐market valuation adjustment for interbank claims, leading to a forward‐backward approach to the equilibrium dynamics whereby future default ...
Zachary Feinstein, Andreas Søjmark
wiley +1 more source
Influence of Observational Temperature Data Sets on ECS and TCR Estimates
Geophysical Research Letters, Volume 53, Issue 12, 28 June 2026.Abstract Uncertainties in estimates of Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR) are influenced by observational temperature data sets. Variability exists not just among the data products, but also within the creation of each one.
Vikrant Sapkota +3 more
wiley +1 more source
AIChE Journal, Volume 72, Issue 6, June 2026.Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi +2 more
wiley +1 more source
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
American Journal of Biological Anthropology, Volume 190, Issue 2, June 2026.Ordered probit regression is used as a latent trait model, with age at death estimated from a Gompertz distribution. Combined with Bayesian Markov Chain Monte Carlo sampling, this approach eliminates the need for reference priors for transition ages or population parameters.
Nils Müller‐Scheeßel +2 more
wiley +1 more source
Bayesian Evaluation of Treatment Effect of Avelumab Plus Axitinib for Advanced Renal Cell Carcinoma
Cancer Medicine, Volume 15, Issue 6, June 2026.ABSTRACT Background Despite not achieving statistical significance, the JAVELIN Renal 101 trial indicated a potentially clinically relevant effect size (hazard ratio [HR], 0.88; 95% confidence interval, 0.75 to 1.04) on overall survival (OS) favoring avelumab plus axitinib over sunitinib for advanced renal cell carcinoma (aRCC).
Wataru Fukuokaya +9 more
wiley +1 more source