kro.inv.test
0.1.2Kronecker-Invariant Tests for High-Dimensional Separability Testing
Overview
Kronecker-invariant tests for high-dimensional separability testing of matrix-variate data, focusing on Gaussian populations as benchmark cases. Tests whether the population covariance matrix is represented as a Kronecker product of row and column covariance matrices. Implements the tests based on the eigenvalues of the sample core whose test statistics are invariant to the separable component of the population covariance matrix, referred to as Kronecker-invariance. Tests constructed using the largest eigenvalue and the separable expansion of the sample core and applying the extended likelihood ratio test for sphericity testing to the sample core. For details, see Sung and Hoff (2025) doi:10.48550/arXiv.2506.17463.
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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
- OK2026-07-165 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
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- Documented parameters
- 100%
- Return-value docs
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- References docs
- 71%
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Code & Tests
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.1.2Latest
- 0.1.12026-07-15
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-15
- Total releases
- 2 / 1 yrs
- License
- GPL-3 OSI
- Download size
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