Future of GaSP R Package
Published in CRAN, 2022
- Currently working with Professor William J. Welch, and Senior Data Scientist Hao Chen to develop Bayesian methods for GaSP 2.0.0, who first published their Bayesian Gaussian Process method on SIAM/ASA Journal.
- The Bayesian methods proposed show some distinct advantages in terms of prediction accuracy and uncertainty quantification and will allow GaSP to be even more flexible.
- Professor William J. Welch and I have plans for version 3.0.0 in the near future.