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-4.4-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)

Peer review:

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

On CRAN:

classificationmachine-learningtwo-sample-test

3 exports 1 stars 0.83 score 1 dependencies 6 scripts 185 downloads

Last updated 4 years agofrom:03415dab65. Checks:OK: 3 NOTE: 4. Indexed: yes.

Exports:empiricalBFHPLBHPLBmatrix

Dependencies:data.table