Debugging and Improving Homothety-Based Prediction Algorithm for Lottery Draws

Hello everyone,

I am working on a MATLAB algorithm that processes past lottery draws from an Excel file (5din40.xlsx). The goal is to predict the next draw using a recursive approach based on homothety coefficients. The algorithm follows these steps:

Import Data: Load n past draws from the Excel file into matrix A[6,2n].

Difference Matrix (DM): Compute first, second, ..., up to 1024th order differences.

Homothety Coefficients (B): Compute homothety constants iteratively using a cross-linked correlation approach.

Solve for Prediction (X): Solve the system X = linesolve(DM, B) to predict the next draw.

Algorithm Details

The homothety coefficients in M are computed iteratively, starting with ones.

Each row updates coefficients using past values to approximate the expected value of the next draw.

The algorithm is repeated across multiple layers until convergence is achieved.

After computing the final set of coefficients, the last computed values are used for prediction.

The same approach is applied for different extracted balls while ensuring no repetition within a single draw.

Issues & Questions

Numerical Stability: The coefficients tend to diverge in some cases—how can I ensure stable convergence?

Efficient Iteration: The iterative update process is slow—are there better ways to optimize these calculations in MATLAB?

Handling Constraints: How can I enforce constraints such as avoiding duplicate ball predictions within a draw?

Gaussian Distribution Check: How can I efficiently implement a check to ensure the predicted sum follows a Gaussian distribution?

Any suggestions or improvements to refine this approach are highly appreciated!

Thanks in advance!

Answer 1

[Viorel-Mihai Popescu]

The files are from Romanian Lotery and the apps need debuging!