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Covariance Measure Tests for Conditional Independence
Covariance measure tests for conditional independence testing against conditional covariance and nonlinear conditional mean alternatives. The package implements versions of the generalised covariance measure test (Shah and Peters, 2020, doi:10.1214/19-aos1857) and projected covariance measure test (Lundborg et al., 2023, doi:10.1214/24-AOS2447). The tram-GCM test, for censored responses, is implemented including the Cox model and survival forests (Kook et al., 2024, doi:10.1080/01621459.2024.2395588). Application examples to variable significance testing and modality selection can be found in Kook and Lundborg (2024, doi:10.1093/bib/bbae475).
- Version0.1-1
- R versionR (≥ 4.2.0)
- LicenseGPL-3
- Needs compilation?No
- Last release01/31/2025
Team
Lucas Kook
MaintainerShow author detailsAnton Rask Lundborg
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 179 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,829 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 08, 2024 with 46 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports5 packages
- Suggests5 packages