Learn how prior probability informs economic theory and decision-making in Bayesian statistics. Understand its role before collecting new data.

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

Abstract: This paper proposes a Bayesian neural network method for predicting equipment operational trends based on a channel attention mechanism. Traditional time series prediction methods have ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...

Researchers at Korea University have developed a machine learning model for predicting sheet resistance in phosphorus oxychloride (POCl3) doping processes in solar cell manufacturing. “Our study aims ...

We develop methodology to bridge scenario analysis and risk forecasting, leveraging their respective strengths in policy settings. The methodology, rooted in Bayesian analysis, addresses the ...

Payment fraud has been high in recent years, and as criminals gain access to capability-enhancing generative AI tools, there is a growing need for innovative fraud detection research. However, the ...

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 ...