TICM
1.0-0Testing the Validity of the Independent Component Model Assumption
Overview
Description: Provides affine-invariant, distribution-free tests of multivariate independence, applied either directly to observed data or to estimated independent components. In the latter case, the procedures can be used to assess the validity of independent component models. The tests are based on L2-type distances between characteristic functions, with inference carried out using permutation or bootstrap resampling schemes. The methods are described in Hallin et al. (2024) doi:10.48550/arXiv.2404.07632.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 75%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0-0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-02-11
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Download size
- 20 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("TICM")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.