agent is behaviorally biased, either neglecting payoff-relevant considerations or updating beliefs in a systematic, non-Bayesian … a Bayesian persuasion framework with a binary safe-versus-risky decision and moderate (monotone) distortions, we show …

In this work, we study n-agent Bayesian games with m-dimensional vector types and linear payoffs, also called linear … multidimensional Bayesian games. This class of games is equivalent with n-agent, m-game uniform multigames. We distinguish between … existence of pure Bayesian Nash equilibriums for such games and efficient algorithms to find them. For continuous priors, we …

-2022 period. Using data from the Fraser Institute and the Manifesto Project Database, we apply a Bayesian time-series methodology …

This document introduces the R library estimateW to estimate spatial weight matrices for Bayesian spatial econometric … estimation approach relies on efficient Bayesian Gibbs sampling techniques and the library supports a variety of the most common …

-normal sensitivity analysis, Internet of Things (IoT)-driven adaptation, and Bayesian Neural Network (BNN) updating to conceptually … modeling, real-time IoT feedback, and Bayesian learning, offering theoretical insights and simulation-based, conceptual …

regressions for 18 Romanian banks over the period 2007Q4 - 2023Q4, a Bayesian Vector Autoregression model for Romania, and a Panel …