For this final blog post, I will write a summary of the final results of my project. The fastest algorithm that I implemented can find the nearest neighbors of one million points and 15 neighbors takes roughly between 20-25 seconds, while the brute force solution would take hours for the same problem. One of the algorithms that I created, the algorithm that uses an unbalanced tree, has been released in the spNNGP R package that can be found on Cran. Overall, this was a very rewarding experience where I had a research project that I had quite a bit of freedom to implement, and get real results. It was great having a project that can be applied to so many real world problems that is used in statistical analysis, and I really enjoyed the experience.