Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

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 ...

WASHINGTON, Nov 14 (Reuters) - The Commerce Department's Bureau of Economic Analysis said on Friday it was working to update its schedule of economic data releases affected by the recently ended ...

This blog post and audio file is another in the series "Defending the Algorithm™" written, edited and narrated by Pittsburgh, Pennsylvania Business, IP and AI Trial Lawyer Henry M. Sneath, Esq. and ...

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 ...

Single-cell transcriptomic architecture for deciphering the complexity of tumor microenvironment in ampulla of Vater carcinoma. Advancing treatment outcomes for peritoneal surface malignancies in low- ...

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 ...

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 ...