Projection Algorithm

In the previously mentioned context, we referenced our custom-developed program. Here we provide a detailed explanation of this program's functionality and background. Our program is designed to process sequential innovation data (difference between observed and predicted values) and perform statistical analysis. Specifically, it calculates the maximum error within innovation sequences through iterative projection operations, and when required, provides relevant correction recommendations using error-bound algorithms. The development background stems from our observation that manual processing of large volumes of innovation data is time-consuming, labor-intensive, and error-prone. The program implements sliding window analysis with error threshold detection, utilizing matrix operations for efficient projection calculations. We believe this program serves as a valuable tool for enhancing the understanding and analysis of innovation sequences in estimation systems, featuring real-time error monitoring and adaptive correction mechanisms.