rbbnp
1.1.0A Bias Bound Approach to Non-Parametric Inference
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2.1Kdownloads / year
0.0%test coverage
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Overview
About
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.
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1NOTE12OK
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- NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 9.1 min · r-devel-linux-x86_64-fedora-clang
Code health
Yes
Tests · ratio 0.75
0.0%
Coverage · measured lines
100%
Documentation · exports
7
Dependencies · direct
Check history
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
Documentation
READMEYes · 213 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
- Examples that run
- 29%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 2%
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Also on100 r2u
Dependencies
Declared dependencies
10 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5
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none
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none
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Package metadata
- First published
- 2024-02-01
- Total releases
- 4 / 2 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 26 KB / 2 files
- Download size
- 254 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet