baggingbwsel: Bagging bandwidth selection in kernel density and regression estimation

This package implements bagging bandwidth selection methods for the Parzen-Rosenblatt kernel density estimator, and for the Nadaraya-Watson and local polynomial kernel regression estimators. These bandwidth selectors can achieve greater statistical precision than their non-bagged counterparts while being computationally fast. See Barreiro-Ures et al. (2021a) and Barreiro-Ures et al. (2021b).

References

Barreiro-Ures, D., Cao, R., Francisco-Fernández, M., & Hart, J. D. (2021a). Bagging cross-validated bandwidths with application to big data. Biometrika, 108(4), 981-988, doi:10.1093/biomet/asaa092 .

Barreiro-Ures, D., Cao, R., & Francisco-Fernández, M. (2021b). Bagging cross-validated bandwidth selection in nonparametric regression estimation with applications to large-sized samples. arXiv preprint, https://arxiv.org/abs/2105.04134.

See also

Useful links:

• https://rubenfcasal.github.io/baggingbwsel/

• https://github.com/rubenfcasal/baggingbwsel/

• Report bugs at https://github.com/rubenfcasal/baggingbwsel/issues/

Author

Maintainer: Ruben Fernandez-Casal rubenfcasal@gmail.com

Authors:

• Daniel Barreiro-Ures daniel.barreiro.ures@udc.es

• Jeffrey Hart

• Ricardo Cao

• Mario Francisco-Fernandez