Version 1.1
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).
Installation
You can install the (compiled) released version from CRAN with:
install.packages("baggingbwsel")Alternatively, you can install the development version from github with:
# install.packages("remotes")
remotes::install_github("rubenfcasal/baggingbwsel")Note also that, as this package requires compilation, Windows users need to have previously installed the appropriate version of Rtools, and OS X users need to have installed Xcode.
Authors
Daniel Barreiro-Ures (daniel.barreiro.ures@udc.es)
Ruben Fernandez-Casal (rubenfcasal@gmail.com)
Jeffrey Hart
Ricardo Cao
Mario Francisco-Fernandez
Maintainer: Ruben Fernandez-Casal (Dep. Mathematics, University of A Coruña, Spain). Please send comments, error reports or suggestions to rubenfcasal@gmail.com.
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, .
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.