rbbnp: A Bias Bound Approach to Non-Parametric Inference

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.