Package: HPLB 1.0.0

HPLB: High-Probability Lower Bounds for the Total Variance Distance

An implementation of high-probability lower bounds for the total variance distance as introduced in Michel & Naef & Meinshausen (2020) <arxiv:2005.06006>. An estimated lower-bound (with high-probability) on the total variation distance between two probability distributions from which samples are observed can be obtained with the function HPLB.

Authors:Loris Michel, Jeffrey Naef

HPLB_1.0.0.tar.gz
HPLB_1.0.0.zip(r-4.5)HPLB_1.0.0.zip(r-4.4)HPLB_1.0.0.zip(r-4.3)
HPLB_1.0.0.tgz(r-4.5-any)HPLB_1.0.0.tgz(r-4.4-any)HPLB_1.0.0.tgz(r-4.3-any)
HPLB_1.0.0.tar.gz(r-4.5-noble)HPLB_1.0.0.tar.gz(r-4.4-noble)
HPLB_1.0.0.tgz(r-4.4-emscripten)HPLB_1.0.0.tgz(r-4.3-emscripten)
HPLB.pdf |HPLB.html
HPLB/json (API)

# Install 'HPLB' in R:
install.packages('HPLB', repos = c('https://lorismichel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lorismichel/hplb/issues

On CRAN:

classificationmachine-learningtwo-sample-test

2.70 score 1 stars 6 scripts 252 downloads 3 exports 1 dependencies

Last updated 5 years agofrom:03415dab65. Checks:3 OK, 5 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 02 2025
R-4.5-winNOTEFeb 02 2025
R-4.5-macNOTEFeb 02 2025
R-4.5-linuxNOTEFeb 02 2025
R-4.4-winNOTEFeb 02 2025
R-4.4-macNOTEFeb 02 2025
R-4.3-winOKFeb 02 2025
R-4.3-macOKFeb 02 2025

Exports:empiricalBFHPLBHPLBmatrix

Dependencies:data.table