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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).
baggingbwsel is not yet available from CRAN, but 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.
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.
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.