SUMMARY
The forum discussion centers on the need for a bivariate smoothing spline package that allows customization of the loss function. Users have noted that existing tools, such as SCIPY, primarily minimize the sum of squared errors, which does not meet their specific requirements. The discussion highlights the desire to maximize the log-likelihood of a Cauchy distribution of errors instead. Participants suggest using black box optimizers to set up custom problems when existing packages do not suffice.
PREREQUISITES
- Understanding of bivariate smoothing splines
- Familiarity with loss functions in statistical modeling
- Knowledge of SCIPY for spline implementation
- Experience with black box optimization techniques
NEXT STEPS
- Research custom loss functions in statistical modeling
- Explore advanced features of SCIPY for spline fitting
- Learn about black box optimization methods and tools
- Investigate alternative packages for bivariate smoothing splines
USEFUL FOR
Data scientists, statisticians, and researchers looking to implement custom loss functions in bivariate smoothing spline models.