Abstract: In the context of Bayesian inversion for scientific and engineering modeling, Markov chain Monte Carlo (MCMC) sampling strategies have become the benchmark due to their flexibility and ...

This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...

Abstract: This paper describes a novel brain and cellular data analysis. Bayesian reasoning and hierarchical models provide important information. Bayesian principles continually anticipate model ...

Objectives To systematically compare the effects of various antithrombotic strategies on prespecified outcomes including 28-day all-cause mortality (primary outcome), major thrombotic events and major ...

Bayesian analysis is being used with increasing frequency in critical care research and brings advantages and disadvantages compared to traditional Frequentist techniques. This study overviews this ...

A James Bond-esque mission to recover highly sensitive secret files held in safes aboard the sunken super-yacht Bayesian was reportedly carried out by UK intelligence service MI6 before Italian divers ...

ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...

Purpose: Bayesian approaches may improve the efficiency of trials and accelerate decision-making, but reluctance to depart from traditional frequentist statistics may limit their use. Because oncology ...

There are two approaches to automatically deriving symbolic worst-case resource bounds for programs: static analysis of the source code and data-driven analysis of cost measurements obtained by ...