“On this classic ID The Future out of the archive, Dr. Jonathan McLatchie gives us a beginner’s guide to Bayesian thinking and teaches us how it can be used to build a strong cumulative case for ...

As we wait for the seabed search for MH370’s wreckage to restart, it’s worth taking the time to reflect about what we’ve learned from the search thus far, and what future scanning will tell us about ...

Currently, ESPresense Companion outputs a single, crisp room assignment per device based on multilateration from RSSI signals. This can be brittle in edge cases (e.g., devices near room boundaries or ...

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 finite second ...

Objectives: We aimed to clarify the influence of facial expressions on providing early recognition and diagnosis of Parkinson’s disease (PD). Methods: We included 18 people with PD and 18 controls.

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

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, ...

This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including ...

The probability of a recession is quite low, maybe at zero, said Jitesh Kumar, derivatives strategist at Societe Generale, in a note. In early August, the U.S. rates market was starting to fully price ...