csmGmm
0.5.0Conditionally Symmetric Multidimensional Gaussian Mixture Model
Overview
Implements the conditionally symmetric multidimensional Gaussian mixture model (csmGmm) for large-scale testing of composite null hypotheses in genetic association applications such as mediation analysis, pleiotropy analysis, and replication analysis. In such analyses, we typically have J sets of K test statistics where K is a small number (e.g. 2 or 3) and J is large (e.g. 1 million). For each one of the J sets, we want to know if we can reject all K individual nulls. Please see the vignette for a quickstart guide. The paper describing these methods is "Testing a Large Number of Composite Null Hypotheses Using Conditionally Symmetric Multidimensional Gaussian Mixtures in Genome-Wide Studies" by Sun R, McCaw Z, & Lin X (Journal of the American Statistical Association 2025, doi:10.1080/01621459.2024.2422124).
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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3 releases. R releases are shown for context.
- 0.5.0Latest
- RR 4.6.0 released · 2026-04-24
- 0.4.02025-09-16 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 0.3.02024-12-03
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-12-03
- Total releases
- 3 / 2 yrs
- License
- GPL-3 OSI
- Download size
- 28 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet