My methodology takes into account a consensus of top analysts and how their earnings estimates have changed over time. Read more here.

What’s often misunderstood about Google’s incrementality testing and how Bayesian models use probability to guide better decisions.

Binary outcomes are frequently encountered in a variety of fields and contexts and the Bayesian approach is widely used to analyze this type of data. Under this framework, a beta prior distribution ...

Heterogeneity among experimental units can introduce experimental errors, necessitating the use of techniques that enhance statistical inferences to address this ...

Abstract: The “k-out-of-n” partially redundant reliability architecture is a flexible and economic configuration for many engineering systems, such as motor drive applications, in various industrial, ...

We consider the high-risk melanoma trial design application in Psioda and Ibrahim (2019), and demonstrate how BayesPPDSurv can be used for coefficient estimation as ...

The BayesPPDSurv (Bayesian Power Prior Design for Survival Data) R package supports Bayesian power and type I error calculations and model fitting using the power and ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

1 Department of Statistics, School of Mathematics, University of Leeds, Leeds, United Kingdom 2 Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of ...

The mathematics that enable sensor fusion include probabilistic modeling and statistical estimation using Bayesian inference and techniques like particle filters, Kalman filters, and α-β-γ filters, ...