Nonparametric regression for functional data provides a flexible statistical framework for modelling relationships between a scalar response and predictors that are inherently functional in nature.

The Annals of Statistics, Vol. 31, No. 3 (Jun., 2003), pp. 880-920 (41 pages) We propose a new test for the comparison of two regression curves that is based on a difference of two marked empirical ...

Kernel estimators of a regression function are investigated. The bandwidths are locally chosen by a data-driven method based on the minimization of a local cross-validation criterion. This method is ...

Nonparametric estimation and U-statistics have emerged as vital tools in modern statistical analysis, offering robust alternatives to traditional parametric methods. Nonparametric techniques bypass ...

SAS/INSIGHT software provides nonparametric curve-fitting estimates from smoothing spline, kernel, loess, and fixed bandwidth local polynomial estimators that are alternatives to fitting polynomials.

Bayesian field theory denotes a nonparametric Bayesian approach for learning functions from observational data. Based on the principles of Bayesian statistics, a particular Bayesian field theory is ...

Doss, Charles R., and Edward McFowland III. "Nonparametric Subset Scanning for Detection of Heteroscedasticity." Journal of Computational and Graphical Statistics 31, no. 3 (2022): 813–823.