Package: rbbnp 0.1.0
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>.
Authors:
rbbnp_0.1.0.tar.gz
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rbbnp.pdf |rbbnp.html✨
rbbnp/json (API)
# Install 'rbbnp' in R: |
install.packages('rbbnp', repos = c('https://dxy99999.r-universe.dev', 'https://cloud.r-project.org')) |
- sample_data - Sample Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:62f848a389. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | OK | Oct 30 2024 |
R-4.5-linux | OK | Oct 30 2024 |
R-4.4-win | OK | Oct 30 2024 |
R-4.4-mac | OK | Oct 30 2024 |
R-4.3-win | OK | Oct 30 2024 |
R-4.3-mac | OK | Oct 30 2024 |
Exports:biasBound_condExpectationbiasBound_densityDATA_PATHEXT_DATA_PATHplot_ft
Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpracmapurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr