The article presents a new algorithm for improving the accuracy of mathematical models used in data analysis. By considering errors in both the data and the model itself, the algorithm provides more precise results compared to traditional methods. The researchers developed an iterative approach based on existing mathematical techniques, which was shown to produce more accurate estimates of parameters and variance in various scenarios. The algorithm was tested in two experiments, demonstrating its effectiveness in nonlinear regression and fitting tasks.