Linear Prediction Model Using Credibility Approach

The paper proposes a linear prediction model based on a credibility approach, which is a strategy for addressing the issue of uncertainty in linear regression models. The credibility approach permits the incorporation of prior knowledge about the linear model’s parameters, resulting in more precise predictions and more accurate uncertainty estimates. Using simulated data and a real-world dataset, the paper demonstrates the efficiency of the proposed methodology. The results indicate that the credibility approach outperforms conventional linear regression models and generates more precise predictions with improved uncertainty estimates. The proposed model has applications in multiple disciplines, including finance, economics, and engineering.