Results 121 to 130 of about 37,630 (219)
Bayesian Inference for Multivariate Monotone Densities
ABSTRACT We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian approach of imposing a prior that satisfies the monotonicity restriction, we place a prior on the step heights via binning and a Dirichlet distribution. The resulting posterior distribution
Kang Wang, Subhashis Ghosal
wiley +1 more source
ABSTRACT A possibly time‐dependent transition intensity matrix or generator (Q(t))$$ \left(Q(t)\right) $$ characterizes the law of a Markov jump process (MP). For a time‐homogeneous MP, the transition probability matrix (TPM) can be expressed as a matrix exponential of Q$$ Q $$.
Dario Gasbarra +2 more
wiley +1 more source
Diagnosing ectopic pregnancy using the bayes theorem and neural network: a validation of a retrospective cohort study. [PDF]
Maroni L, Silva PC, Kunst R, Savaris RF.
europepmc +1 more source
Abstract Background Many mitigation processes have been introduced to reduce septic transfusion reactions (STRs) caused by the transfusion of bacterially contaminated PLTs. Methods The efficacy of primary culture and pathogen reduction is assessed in this review using data from long‐term hemovigilance programs in the US, Canada, UK, France, Switzerland,
Michael R. Jacobs
wiley +1 more source
Correction to: A software tool for applying Bayes' theorem in medical diagnostics. [PDF]
Chatzimichail T, Hatjimihail AT.
europepmc +1 more source
Frequency‐dependent contraction rates for the Bayesian method to the inverse source problem
Abstract This paper addresses an inverse source problem for acoustic waves in a range of frequencies. Our study has two main goals. First, although the problem is severely ill‐posed with a logarithmic stability estimate, we demonstrate, through careful analysis of the forward map's singular values, that increasing the frequency range enhances stability,
Pu‐Zhao Kow, Jenn‐Nan Wang
wiley +1 more source
Use of Bayesian Networks for the Forensic Evaluation of Gunshot Residue
Bayesian Networks can help evaluate gunshot residue given activity level propositions. This review discusses the different approaches that have been taken in the past and the challenges we are facing, with recommendations for future research. ABSTRACT Gunshot residue is a common type of trace considered in forensic science.
Yingxiu Guo +2 more
wiley +1 more source

