Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

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.

Frequentist methods, without the coherence guarantees of fully Bayesian methods, are known to yield self-contradictory inferences in certain settings. The framework introduced in this paper provides a ...

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, ...

Bayesian species-tree inference with StarBEAST2 In this part of the tutorial, we are going to use the multi-species-coalescent model implementation of StarBEAST2 (Ogilvie et al. 2017) to estimating a ...

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

Recursive Bayesian inference, in which posterior beliefs are updated in light of accumulating data, is a tool for implementing Bayesian models in applications with streaming and/or very large data ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

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 ...

Perceptual judgments of ambiguous stimuli are often biased by prior expectations. These biases may offer a window into the neural computations that give rise to perceptual interpretations of the ...