Understanding PS-MC Algorithm [Implementing PS-MC]

[sarahnourgh]

• Thoroughly read and understand the description of the PS-MC method provided in the research article.
• Identify the key components, parameters, and mathematical formulations of the algorithm.

⚠ Remark:

• Optimize Computational Efficiency:
• Optimize the computational efficiency of the PS-MC algorithm by minimizing redundant computations and memory usage.
• Utilize parallelization techniques to speed up computations, such as multi-threading or distributed computing.
• Debug and Test Implementation:
• Debug the code to identify and fix any errors, bugs, or inconsistencies in the implementation.
• Test the PS-MC algorithm with synthetic data or simple examples to verify its correctness and functionality.
• Documentation and Reporting:
• Document the PS-MC algorithm, including its implementation details, input parameters, and usage instructions.
• Report the results obtained from the PS-MC method in the project documentation or research report, along with any relevant insights or observations.

🥅 The Goal:
the Path Shadowing Monte-Carlo (PS-MC) method and apply it to predict future paths and compute quantities of interest based on the generative model.