The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
A novel bias-bound approach for non-parametric inference is introduced, focusing on both density and conditional expectation estimation. It constructs valid confidence intervals that account for the presence of a non-negligible bias and thus make it possible to perform inference with optimal mean squared error minimizing bandwidths. This package is based on Schennach (2020) <doi:10.1093/restud/rdz065>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5) |
| Imports: | purrr, pracma, tidyr, dplyr, ggplot2, gridExtra |
| Published: | 2024-02-01 |
| DOI: | 10.32614/CRAN.package.rbbnp |
| Author: | Xinyu DAI [aut, cre], Susanne M Schennach [aut] |
| Maintainer: | Xinyu DAI <xinyu_dai at brown.edu> |
| License: | GPL (≥ 3) |
| URL: | https://doi.org/10.1093/restud/rdz065 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | rbbnp results |
| Reference manual: | rbbnp.pdf |
| Package source: | rbbnp_0.1.0.tar.gz |
| Windows binaries: | r-devel: rbbnp_0.1.0.zip, r-release: rbbnp_0.1.0.zip, r-oldrel: rbbnp_0.1.0.zip |
| macOS binaries: | r-release (arm64): rbbnp_0.1.0.tgz, r-oldrel (arm64): rbbnp_0.1.0.tgz, r-release (x86_64): rbbnp_0.1.0.tgz, r-oldrel (x86_64): rbbnp_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=rbbnp to link to this page.
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.
Health stats visible at Monitor.