Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...
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 ...
Heterogeneity among experimental units can introduce experimental errors, necessitating the use of techniques that enhance statistical inferences to address this issue. One effective approach is ...
Mathematics Department, Egerton University, Njoro Nakuru, Kenya. Bayesian techniques have been applied in many epidemiological settings, such as disease monitoring, outbreak simulation, and prevalence ...
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, ...
Abstract: This work studies an information-theoretic performance limit of an integrated sensing and communication (ISAC) system where the goal of sensing is to ...
Abstract: The Bayesian Cramér-Rao bound (CRB) provides a lower bound on the mean square error of any Bayesian estimator under mild regularity conditions. It can be ...
Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...
The folder contains examples and codes developed in the Willy Mutchler lecture's at the Tübingen University . The course deals with estimation of SVAR and DSGE models ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback